Relevant bibliographies by topics / Radiography, Medical – Digital techniques

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Radiography, Medical – Digital techniques'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 January 2023

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Journal articles on the topic "Radiography, Medical – Digital techniques"

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Yahaghi, Effat, Amir Movafeghi, Shokoofeh Ahmadi, Sholeh Ansari, Mehran Taheri, and Naser Rastkhah. "Cultural Heritage Object Identification by Radiography Nondestructive Method and Digital Image Processing." Applied Mechanics and Materials 83 (July 2011): 35–40. http://dx.doi.org/10.4028/www.scientific.net/amm.83.35.

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Nondestructive testing (NDT) is an important tool in the world of industry. Among different NDT methods, radiography plays a very interesting role both in industry and medicine. Medical and industrial uses of X and gamma rays were recognized since more than 1 century ago. One of the interesting uses of radiography is in archeological and art applications. In this research, radiography was utilized for identification of a damaged art-historical material. The subject is a brass tray belonging to Iran cultural heritage with an estimated age of about 3500 years. The tray was found in Lorestan province and referred to as “Lorestan bonze”. The object was damaged seriously due to heavy corrosion attack. Therefore recognition of the object was a major problem. Normal radiography method can help for object determination, but it suffers some major drawbacks related to contrast and thickness measurement. Image processing technique and a precise thickness measurement method were added to digitized radiographs. A precise radiographic thickness method was introduced and used before for the pipeline radiography. For digital image processing, Canny edge detection method and Gaussian filter were used. Radiography image obtained from this work showed a very clear picture of the original trace of hammered design. These results showed that a combination of radiography, image processing techniques and consideration of physical principles of radiation interaction with materials can produce a very clear image which can be used effectively for hte detail analysis of cultural heritages.
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Yazdanian, Mohsen, Shahryar Karami, Elahe Tahmasebi, Mostafa Alam, Kamyar Abbasi, Mahdi Rahbar, Hamid Tebyaniyan, Reza Ranjbar, Alexander Seifalian, and Alireza Yazdanian. "Dental Radiographic/Digital Radiography Technology along with Biological Agents in Human Identification." Scanning 2022 (January 18, 2022): 1–30. http://dx.doi.org/10.1155/2022/5265912.

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The heavy casualties associated with mass disasters necessitate substantial resources to be managed. The unexpectedly violent nature of such occurrences usually remains a problematic amount of victims that urgently require to be identified by a reliable and economical method. Conventional identification methods are inefficient in many cases such as plane crashes and fire accidents that have damaged the macrobiometric features such as fingerprints or faces. An appropriate recognition method for such cases should use features more resistant to destruction. Forensic dentistry provides the most appropriate available method for the successful identification of victims using careful techniques and precise data interpretation. Since bones and teeth are the most persistent parts of the demolished bodies in sudden mass disasters, scanning and radiographs are unrepeatable parts of forensic dentistry. Forensic dentistry as a scientific method of human remain identification has been considerably referred to be efficient in disasters. Forensic dentistry can be used for either “sex and age estimation,” “Medical biotechnology techniques,” or “identification with dental records,” etc. The present review is aimed at discussing the development and implementation of forensic dentistry methods for human identification. For this object, the literature from the last decade has been searched for the innovations in forensic dentistry for human identification based on the PubMed database.
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Oyedeji, A. I., B. J. Adenle, and O. I. Ifeka. "Assessment On Digital Imaging Enhancement For Radiographic Interpretation." Advances in Multidisciplinary and scientific Research Journal Publication 29 (December 15, 2021): 141–52. http://dx.doi.org/10.22624/aims/abmic2021p11.

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In recent time digital imaging systems are the most commonly utilized technology in the field of radiology. The screen-film radiography systems are almost replaced by digital radiography. In which the image quality should be optimized while lower radiation dose is maintained according to the properties of the specific imaging system. Therefore, it is essential to regularly investigate image quality to ensure correct and accurate image interpretation assessment. This research is aimed to assess the factors that influence image quality and to recognize the different evaluation methods and their corresponding approaches that are used for system performance. Resolution describes the ability of medical imaging process to discriminate adjacent structures in organ tissues being examined. Signal from detected photon should be recorded with sufficient resolution in space, intensity and possibly time to produce a digital image that enables a medical interpretation of tissue structure and function. The anatomical and physiological characteristics of the region being imaged are considered to be the intrinsic factors of image contrast, which are called intrinsic, subject, object, or patient contrast. Low intrinsic contrast tissues such as breast tissues have very subtle differences in composition. In radiography, the physical properties of atomic number, physical density differences among different tissues and patient thickness influence intrinsic or subject contrast. Imaging methods and techniques are the second major factor which control image contrast. Will be more appropriate to select careful exposure techniques for specific tissues and for certain purposes greatly enhances image contrast to obtain the desired information. The only way to optimize image quality parameters while maintaining low radiation dose is to deeply understand the effects of these parameters on each other, the influence factors and their impact on the radiation dose for each different digital radiographic systems.[5] Keywords: Assessment, Image Enhancement, Radiology, Digital, Technology
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Hsiao, Wen-Tien, Wen-Chi Kuo, Hsin-Hon Lin, and Lu-Han Lai. "Assessment and Feasibility Study of Lemon Ripening Using X-ray Image of Information Visualization." Applied Sciences 11, no. 7 (April 6, 2021): 3261. http://dx.doi.org/10.3390/app11073261.

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Digital radiography (DR) is a mature technology and has been broadly used in medical diagnosis. Currently, it’s also used for fruit quality inspection in the market. This purpose of the study is to conduct non-destructive experiments for visual comparisons of digital radiography images, further construct visualized grayscale image analysis technology, and analyze the changes in lemon quality and ripening using quantitative statistical methods. The materials used for the experiments were three lemons of different ripening. A general medical X-ray DR system for was used in this study for 2D digital radiography. The medical X-ray DR images were created based on the Digital Imaging and Communications in Medicine (DICOM) standard. Photometric interpretation of monochrome was applied to create multi-layered grayscale images. Then quantitative analyses and comparisons were performed with image matrix structures and grayscale pixel values in the tissues using visualization techniques and statistical methods. After layer segmentation on the radiological images, the correlations between the lemon structures and tissue changes were assessed by using the Kruskal–Wallis test. The results showed that the p values for lemon, fiber, and pulp were all under 0.05, while the peel layer did not exhibit significant change. The pulp layer is the best region for statistical analyses to determine the lemon ripening. In conclusion, this study can provide a solid reference for future quality classification in the agricultural market. The research findings can be referenced for developing computing techniques applied to agricultural inspection, expanding the scope of application of the medical DR technology.
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Ilic, Dragan, and Ljiljana Stojanovic. "Application of radiovisiography (digital radiology) in dental clinical practice." Vojnosanitetski pregled 69, no. 1 (2012): 81–84. http://dx.doi.org/10.2298/vsp1201081i.

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Introduction. Radiovisiography (RVG) as the latest imaging technique in dentistry with the minimal radiation exposure of the patient and numerous possibilities to process the images has many advantages over classic radiography. Case report. We presented an interesting clinical endodontic case of primary posted diagnosis of traumatic periodontitis of upper right canine upon orthodontics treatment. As the patient previously had been exposed to alleged high dose of radiation the patient agreed to minimal exposition using digital RVG. The options of the tool bar of RVG Trophy device enabled the solving of ethiologic factor of presented periodontitis. The enigma of the symptoms on the ?overfilled? root canal was solved zooming and 3-D analysis avoiding periapical surgery owing to the patience of the patient and the dentist in a couple of days. Conclusion. By applying RVG technique the time for diagnostic procedure is much shorter in comparison with traditional dental radiography enabling archiving and follow-up the presented case in the course of time.
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Serena Low, Woan Ching, Joon Huang Chuah, Clarence Augustine T. H. Tee, Shazia Anis, Muhammad Ali Shoaib, Amir Faisal, Azira Khalil, and Khin Wee Lai. "An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19." Computational and Mathematical Methods in Medicine 2021 (June 4, 2021): 1–17. http://dx.doi.org/10.1155/2021/5528144.

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Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant’s technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases.
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AKDENİZ, Berat Serdar, Yunus ÇARPAR, and Kübra ARSLAN ÇARPAR. "Digital three-dimensional planning of orthodontic miniscrew anchorage: A literature review." Journal of Experimental and Clinical Medicine 39, no. 1 (January 1, 2022): 269–74. http://dx.doi.org/10.52142/omujecm.39.1.50.

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Orthodontic miniscrews are used for skeletal orthodontic anchorage. An appropriate insertion technique is essential to avoid complications during miniscrew placement. The guides prepared using surface anatomy and 2D radiographs cannot correctly analyze bone volume. Advances in digital 3D medical technologies enabled orthodontists to use digital imaging, digital scanning, and 3D printing to accurately place miniscrews using a surgical guide developed with computer-aided design and manufacturing techniques. The objective of this article was to demonstrate the development of miniscrew placement techniques chronologically and provide brief information about the production, use, and efficiency of modern, digitally planned, and produced miniscrew insertion guides.
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Saccomanno, Sabina, Pier Carmine Passarelli, Bruno Oliva, and Cristina Grippaudo. "Comparison between Two Radiological Methods for Assessment of Tooth Root Resorption: An In Vitro Study." BioMed Research International 2018 (2018): 1–7. http://dx.doi.org/10.1155/2018/5152172.

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Purpose. This study aims to verify the validity of the radiographic image and the most effective radiological techniques for the diagnosis of root resorption to prevent, cure, and reduce it and to verify if radiological images can be helpful in medical and legal situations. Methods. 19 dental elements without root resorption extracted from several patients were examined: endooral and panoramic radiographs were performed, with traditional and digital methods. Then the root of each tooth was dipped into 3-4 mm of 10% nitric acid for 24 hours to simulate the resorption of the root and later submitted again to radiological examinations and measurements using the same criteria and methods. Results. For teeth with root resorption the real measurements and the values obtained with endooral techniques and digital sensors are almost the same, while image values obtained by panoramic radiographs are more distorted than the real ones. Conclusions. Panoramic radiographs are not useful for the diagnosis of root resorption. The endooral examination is, in medical and legal fields, the most valid and objective instrument to detect root resorption. Although the literature suggests that CBCT is a reliable tool in detecting root resorption defects, the increased radiation dosage and expense and the limited availability of CBCT in most clinical settings accentuate the outcome of this study.
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Privalov, M., and M. Stupina. "Application of the transfer learning to the medical images texture classification task." E3S Web of Conferences 224 (2020): 01020. http://dx.doi.org/10.1051/e3sconf/202022401020.

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This study is conducted to determine effectiveness and perspectives of application of the transfer learning approach to the medical images classification task. There are a lot of medical studies that involve image acquisition, such as XRay radiography, ultrasonic scanning, computer tomography (CT), magnetic resonance imaging (MRI) etc. Besides those medical procedures there are different operations that use medical images processing including but not limited to digital radiograph reconstruction (DRR), radiotherapy planning, brachy therapy planning. All those tasks could be effectively performed with help of software capable to perform segmentation, classification and object recognition. Those capabilities are naturally depend on neural classifiers. Presented work investigates different approaches to solving image classification task with neural networks, specifically, using pre-processing for feature extraction and end-to-end application of convolutional neural networks (CNN). Due to requirement of significantly big datasets and large computing power CNNs sometimes may appear difficult to train, so our results pay attention to application of transfer learning technique that can potentially relax requirements to classifier training. The conclusions of this study state that transfer learning can be effectively used for classification tasks, especially texture classification.
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Kaushik, Chanchal, Inderjeet Singh Sandhu, A. K. Srivastava, and Mansi Chitkara. "ESTIMATION OF ENTRANCE SURFACE AIR KERMA IN DIGITAL RADIOGRAPHIC EXAMINATIONS." Radiation Protection Dosimetry 193, no. 1 (January 2021): 16–23. http://dx.doi.org/10.1093/rpd/ncab018.

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Abstract Purpose: Contribution of radiation doses from medical X-ray examination to collective dose is significant. Unusually, high doses may increase the risk of stochastic effects of radiations. Therefore, radiation dose assessment was performed in 241 digital X-ray examinations in the study and was compared with published dose reference levels (DRLs). Methods: Entrance surface air kerma (ESAK) was calculated in chest PA, cervical AP/Lat, abdomen AP, lumbar AP/Lat and pelvis AP digital radiographic examinations (119 male and 122 female) following the International Atomic Energy Agency recommended protocol. Initially, 270 digital examinations were selected, reject analysis was performed and final 241 examinations were enrolled in the study for dose calculations. The exposure parameters and X-ray tube output were used for dose calculations. Effective doses were estimated with the help of conversion coefficients from ICRP 103. Results: Median ESAK (mGy) and associated effective doses obtained were cervical spine AP (1.30 mGy, 0.045 mSv), cervical spine Lat (0.25 mGy, 0.005 mSv), chest PA (0.11 mGy, 0.014 mSv), abdomen AP (0.90 mGy, 0.118 mSv), lumbar spine AP (1.52 mGy, 0.177 mSv), lumbar spine Lat (7.76 mGy, 0.209 mSv) and pelvis AP (0.82 mGy, 0.081 mSv). Results were compared with the studies of UK, Oman, India and Canada. Conclusion: The calculated ESAK and effective dose values were less than or close to previously published literature except for cervical spine AP and lumbar spine Lat. The results reinforce the need for radiation protection optimization, improving examination techniques and appropriate use of automatic exposure control in digital radiography. ESAK values reported in this study could further contribute to establishing local DRLs, regional DRLs and national DRLs.
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Dissertations / Theses on the topic "Radiography, Medical – Digital techniques"

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Campbell, Sydney. "Experiences of analogue-trained radiographers utilising digital imaging in projection radiography." Thesis, Nelson Mandela Metropolitan University, 2017. http://hdl.handle.net/10948/14796.

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The professional work of a radiographer encompasses both patient care and the use of technology. The technology employed could either be analogue or digital technology. Since 1973, the analogue imaging system has slowly been replaced by digital radiography imaging systems. Despite the many advantages of digital imaging it does present the radiographer with added responsibilities. Furthermore, analogue-trained radiographers have found adjusting to digital imaging especially challenging. The aim of the study was to explore and describe the experiences of analogue-trained radiographers utilising digital imaging in projection radiography with the intention of developing guidelines to equip radiography managers to assist analogue-trained radiographers to better utilise digital imaging. The researcher used Schlossberg’s Transition Theory as a lens to look at the experiences of analogue-trained radiographers using digital imaging to produce radiographs. The research study used a qualitative design which was explorative, descriptive and contextual in nature. The target population included all diagnostic radiographers (public and private) in the local municipality who were registered with the Health Professions Council of South Africa. Purposive sampling was employed to select the radiographers that represented all radiographers in the Nelson Mandela Bay Health District. The sample included all radiographers who fulfilled the identified selection criteria. The selected participants were recruited to take part in in-depth, semi-structured individual interviews. The data was analysed using a computer-aided qualitative data analysis software package, ATLAS.ti. The trustworthiness of this study was ensured by applying Guba’s model of trustworthiness that includes credibility, transferability, dependability and confirmability. The ethical principles of respect for persons, beneficence and justice, as espoused by the Belmont Report, were adhered to in order to ensure that the study was conducted in an ethical manner. Two themes emanated from the data, namely the evolution of the radiographer when faced with the advances in technology as well the role that the work environment played in the manner that the participants experienced the change. The experiences of the participants were described using direct quotations from the interviews and a literature control was used to verify the participants’ experiences. Evidence was found of radiographer indifference towards exposure selection, dose optimisation and placement of anatomical side markers when utilising digital imaging. Finally, guidelines were developed to equip radiography managers to assist analogue-trained radiographers to better utilise digital imaging. In addition, the guidelines will assist all other radiographers to better utilise digital imaging.
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Batuka, Nabawesi Jennifer. "Pre and post computerized radiography film reject analysis in a private hospital in Kenya." Thesis, Nelson Mandela Metropolitan University, 2011. http://hdl.handle.net/10948/1574.

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The production of good quality radiographs is a complex process, given the high level of image quality required (Sniureviciute & Adliene, 2005: 260). Exposure of patients to x-rays, a factor in the production of quality radiographs also entails a risk of radiation injury. In 2006, computerized radiography (CR) was introduced at The Nairobi Hospital to try and reduce the film reject rate, decrease repeats, reduce financial costs of consumables like x-ray films and processing chemicals. However, to date, no formal film reject analysis has been conducted at The Nairobi Hospital. Four years after the incorporation of CR, there is apparently, still a significant number of film rejects, implying operational costs may still be high. The cause of film rejects and overall reject cost is not known. This has led to the research question: “Has the film reject rate in the A & E x-ray unit at The Nairobi Hospital reduced following incorporation of CR?” A quantitative, retrospective, descriptive study involving a reject film analysis of rejected radiographs in the Accident and Emergency (A&E) x-ray unit in the Nairobi Hospital, Kenya was conducted. The researcher collected data for a period of 6 months between 2/12/07 and 28/05/08 using a purpose-designed data collection form. All rejected x-ray films during the study period were included. Capture and analysis of the collected data was completed by the researcher using SPSS 10 and EPINFO computer packages. Permission to conduct the study was obtained from The Nairobi Hospital Education Committee and due consideration to patient and radiographer confidentiality was maintained throughout the study. A total of 851(2.5 percent) x-ray films were collected during the study period. Four hundred and fourteen (2.6 percent) radiographs and 437 (2.5 percent) radiographs were rejected prior to and after the incorporation of CR respectively. Chest radiographs were the most frequently rejected accounting for 277(66.9 percent) and 123 (28.1 percent) prior to and after the incorporation of CR respectively. The most frequently rejected film size was 35x35cm prior to the incorporation of CR (61.6 percent) and 26x35cm film size after the incorporation of CR (91.3 percent). The most frequent cause of film rejects was radiographer causes both prior to and after the incorporation of CR accounting for 496 (58.3 percent). The film reject rate did not significantly reduce after the incorporation of CR, suggesting that there are other factors which contribute to reject rate, other than CR. The study also shows that higher film consumption does not necessarily lead to high reject rates. The percentage value on annual rejects did not change after the incorporation of CR and a demonstrated increase in the annual cost of purchasing x-ray films was attributed to an increase in annual consumption after the incorporation of CR, and also to the higher cost of digital x-ray films. Despite some identified limitations to this study, some recommendations, which included conduction of regular reject analyses and regular continuing professional development with respect to radiographic technique amongst others, were suggested.
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Woo, Mei-sum Becky, and 胡美心. "Validation and calibration of a digital subtraction radiography systemfor quantitative assessment of alveolar bone changes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31954169.

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Rehm, Kelly. "Development and image quality assessment of a contrast-enhancement algorithm for display of digital chest radiographs." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/185844.

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This dissertation presents a contrast-enhancement algorithm called Artifact-Suppressed Adaptive Histogram Equalization (ASAHE). This algorithm was developed as part of a larger effort to replace the film radiographs currently used in radiology departments with digital images. Among the expected benefits of digital radiology are improved image management and greater diagnostic accuracy. Film radiographs record X-ray transmission data at high spatial resolution, and a wide dynamic range of signal. Current digital radiography systems record an image at reduced spatial resolution and with coarse sampling of the available dynamic range. These reductions have a negative impact on diagnostic accuracy. The contrast-enhancement algorithm presented in this dissertation is designed to boost diagnostic accuracy of radiologists using digital images. The ASAHE algorithm is an extension of an earlier technique called Adaptive Histogram Equalization (AHE). The AHE algorithm is unsuitable for chest radiographs because it over-enhances noise, and introduces boundary artifacts. The modifications incorporated in ASAHE suppress the artifacts and allow processing of chest radiographs. This dissertation describes the psychophysical methods used to evaluate the effects of processing algorithms on human observer performance. An experiment conducted with anthropomorphic phantoms and simulated nodules showed the ASAHE algorithm to be superior for human detection of nodules when compared to a computed radiography system's algorithm that is in current use. An experiment conducted using clinical images demonstrating pneumothoraces (partial lung collapse) indicated no difference in human observer accuracy when ASAHE images were compared to computed radiography images, but greater ease of diagnosis when ASAHE images were used. These results provide evidence to suggest that Artifact-Suppressed Adaptive Histogram Equalization can be effective in increasing diagnostic accuracy and efficiency.
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Vercillo, Richard 1953. "Very high resolution video display memory and base image memory for a radiologic image analysis console." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276707.

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Digital radiographic images are created by a variety of diagnostic imaging modalities. A multi-modality workstation, known as the Arizona Viewing Console (AVC), was designed and built by the University of Arizona Radiology Department to support research in radiographic image processing and image display. Two specially designed VMEbus components, the base image memory and the video display memory, were integrated into the AVC and are the subject of this thesis. The base image memory is a multi-ported, 8 megabyte memory array based on random access memory used for raw image storage. It supports a 10 megapixel per second image processor and can interface to a 320 megabit per second network. The video display memory utilizes video memories and is capable of displaying two independent high resolution images, each 1024 pixels by 1536 lines, on separate video monitors. In part, these two memory designs have allowed the AVC to excel as a radiographic image workstation.
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Masek, Martin. "Hierarchical segmentation of mammograms based on pixel intensity." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2003.0033.

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Mammography is currently used to screen women in targeted risk classes for breast cancer. Computer assisted diagnosis of mammograms attempts to lower the workload on radiologists by either automating some of their tasks or acting as a second reader. The task of mammogram segmentation based on pixel intensity is addressed in this thesis. The mammographic process leads to images where intensity in the image is related to the composition of tissue in the breast; it is therefore possible to segment a mammogram into several regions using a combination of global thresholds, local thresholds and higher-level information based on the intensity histogram. A hierarchical view is taken of the segmentation process, with a series of steps that feed into each other. Methods are presented for segmentation of: 1. image background regions; 2. skin-air interface; 3. pectoral muscle; and 4. segmentation of the database by classification of mammograms into tissue types and determining a similarity measure between mammograms. All methods are automatic. After a detailed analysis of minimum cross-entropy thresholding, multi-level thresholding is used to segment the main breast tissue from the background. Scanning artefacts and high intensity noise are separated from the breast tissue using binary image operations, rectangular labels are identified from the binary image by their shape, the Radon transform is used to locate the edges of tape artefacts, and a filter is used to locate vertical running roller scratching. Orientation of the image is determined using the shape of the breast and properties of the breast tissue near the breast edge. Unlike most existing orientation algorithms, which only distinguish between left facing or right facing breasts, the algorithm developed determines orientation for images flipped upside down or rotated onto their side and works successfully on all images of the testing database. Orientation is an integral part of the segmentation process, as skin-air interface and pectoral muscle extraction rely on it. A novel way to view the skin-line on the mammogram is as two sets of functions, one set with the x-axis along the rows, and the other with the x-axis along the columns. Using this view, a local thresholding algorithm, and a more sophisticated optimisation based algorithm are presented. Using fitted polynomials along the skin-air interface, the error between polynomial and breast boundary extracted by a threshold is minimised by optimising the threshold and the degree of the polynomial. The final fitted line exhibits the inherent smoothness of the polynomial and provides a more accurate estimate of the skin-line when compared to another established technique. The edge of the pectoral muscle is a boundary between two relatively homogenous regions. A new algorithm is developed to obtain a threshold to separate adjacent regions distinguishable by intensity. Taking several local windows containing different proportions of the two regions, the threshold is found by examining the behaviour of either the median intensity or a modified cross-entropy intensity as the proportion changes. Image orientation is used to anchor the window corner in the pectoral muscle corner of the image and straight-line fitting is used to generate a more accurate result from the final threshold. An algorithm is also presented to evaluate the accuracy of different pectoral edge estimates. Identification of the image background and the pectoral muscle allows the breast tissue to be isolated in the mammogram. The density and pattern of the breast tissue is correlated with 1. Breast cancer risk, and 2. Difficulty of reading for the radiologist. Computerised density assessment methods have in the past been feature-based, a number of features extracted from the tissue or its histogram and used as input into a classifier. Here, histogram distance measures have been used to classify mammograms into density types, and ii also to order the image database according to image similarity. The advantage of histogram distance measures is that they are less reliant on the accuracy of segmentation and the quality of extracted features, as the whole histogram is used to determine distance, rather than quantifying it into a set of features. Existing histogram distance measures have been applied, and a new histogram distance presented, showing higher accuracy than other such measures, and also better performance than an established feature-based technique.
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Ved, Hetal R. "A computer-based cascaded modeling and experimental approach to the physical characterization of a clinical full-field mammography system." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-0920102-144012.

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Wu, Bangxian, and 吴邦限. "Clinical applications of imaging informatics: computer aided diagnosis of nasopharyngeal carcinoma based on PET-CTand multimedia electronic patient record system for neurosurgery." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48521917.

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Medical imaging informatics is one of the important research areas in radiology that studies how information available on medical images is retrieved, analyzed, and enhanced. Recent development in medical imaging informatics has resulted in improvement of diagnostic accuracy based on imaging examinations, as well as efficiency in clinical workflow. Computer aided diagnosis (CAD) and electronic patient record system (ePR) are both topics in medical imaging informatics that have matured from research concepts into commercially available computerized systems in clinical environment. The current challenges are to further broaden their scope of applications. In this thesis project, I developed a CAD system for interpreting PET/CT examinations and an ePR system for patient data integration in neurosurgery suites. Specifically, the CAD system in this project was designed to automatically diagnose nasopharyngeal carcinoma (NPC) on Positron emission tomography/computed tomography (PET/CT) examinations, which aimed to detect and classify both the primary NPC and its nodal metastasis. The regions of interests (ROIs) were segmented from the PET images and registered onto the CT in order to combine the imaging features from both modalities and the a priori anatomical knowledge of the suspicious lesion. These combined features were then classified by a support vector machine (SVM) to generate the final diagnosis result. The system was validated with 25 PET/CT examinations from 10 patients suffering from NPC, and the result produced by the system was compared to the gold standard of lesions manually contoured by experienced radiologists. The results confirmed that the system successfully distinguished all 53 genuine lesions from the mimickers due to normal physiological uptake and artifacts that also produced potentially confusing signals. The second part of the project involved development of an electronic patient record system (ePR) that integrated all the myriad of images and different types of clinical information before, during, and after neurosurgery operations, in order to enhance efficiency of work flow in this unique clinical environment. The system comprises of pre-, intra-, and post-operation modules which correspond to the different stages of the neurosurgery. The pre-op module was developed to store and categorize all images and data before the procedure to assist the surgeons in planning operation. The intra-op module integrates all the input signals, waveforms, images and videos that are produced by different imaging and physiological monitoring devices in the operation room during the surgery, and displays all the relevant information in a single large screen in real time to ease monitoring of the procedure. The post-op module helps surgeons to review all the data acquired from all the prior stages for follow-up of the treatment outcome. One-tumor case was utilized to test the pre-op module, and the signals and waveforms simulators were used to evaluate the performance of the intra-op module. In summary, two different medical informatics systems, a CAD and an ePR system were developed. Both showed promising results in laboratory tests. Future work would involve performance enhancement and feedback of the systems, and ultimately evaluation of these systems in the clinical environment.
published_or_final_version
Diagnostic Radiology
Master
Master of Philosophy
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Leal, Michael J. "Effect of pixel size and scintillator on image quality of a CCD-based digital x-ray imaging system." Link to electronic thesis, 2001. http://www.wpi.edu/Pubs/ETD/Available/etd-0502101-123456.

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Wake, Giulia M. G. H. "Exact minimisation of treatment time for the delivery of intensity modulated radiation therapy." University of Western Australia. School of Mathematics and Statistics, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0195.

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This thesis investigates the exact minimisation of treatment delivery time for Intensity Modulated Radiation Therapy (IMRT) for the treatment of cancer using Multileaf Collimators (MLC). Although patients are required to remain stationary during the delivery of IMRT, inevitably some patient movement will occur, particularly if treatment times are longer than necessary. Therefore minimising the treatment delivery time of IMRT may result in less patient movement, less inaccuracy in the dosage received and a potentially improved outcome for the patient. When IMRT is delivered using multileaf collimators in 'step and shoot' mode, it consists of a sequence of multileaf collimator configurations, or shape matrices; for each, time is needed to set up the configuration, and in addition the patient is exposed to radiation for a specified time, or beam-on time. The 'step and shoot leaf sequencing' problems for minimising treatment time considered in this thesis are the constant set-up time Total Treatment Time (TTT) problem and the Beam-on Time Constrained Minimum Cardinality (BTCMC) problem. The TTT problem minimises a weighted sum of total beam-on time and total number of shape matrices used, whereas the BTCMC problem lexicographically minimises the total beam-on time then the number of shape matrices used in a solution. The vast majority of approaches to these strongly NP-hard problems are heuristics; of the few exact approaches, the formulations either have excessive computation times or their solution methods do not easily incorporate multileaf collimator mechanical constraints (which are present in most currently used MLC systems). In this thesis, new exact mixed integer and integer programming formulations for solving the TTT and BTCMC problems are developed. The models and solution methods considered can be applied to the unconstrained and constrained versions of the problems, where 'constrained' refers to the modelling of additional MLC mechanical constraints. Within the context of integer programming formulations, new and existing methods for improving the computational efficiency of the models presented are investigated. Numerical results for all variations considered are provided. This thesis demonstrates that significant computational improvement can be achieved for the exact mixed integer and integer programming models investigated, via solution approaches based on an idea of systematically 'stepping-up' through the number of shape matrices used in a formulation, via additional constraints (particularly symmetry breaking constraints) and via the application of improved bounds on variables. This thesis also makes a contribution to the wider field of integer programming through the examination of an interesting substructure of an exact integer programming model. In summary, this thesis presents a thorough analysis of possible integer programming models for the strongly NP-hard 'step and shoot' leaf sequencing problems and investigates and applies methods for improving the computational efficiency of such formulations. In this way, this thesis contributes to the field of leaf sequencing for the application of Intensity Modulated Radiation Therapy using Multileaf Collimators.
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Books on the topic "Radiography, Medical – Digital techniques"

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Peter, Busch Hans, and Georgi M, eds. Digital radiography: Clinical experiences with digital image intensifier and storage phosphor radiology. Berlin: Blackwell Wissenschaft, 1992.

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L, Vealé Beth, ed. Digital radiography and PACS. St. Louis, Mo: Mosby Elsevier, 2008.

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L, Vealé Beth, ed. Digital radiography and PACS. St. Louis, Mo: Mosby/Elsevier, 2010.

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International, Workshop on Digital Mammography (3rd 1996 Chicago Ill ). Digital mammography '96: Proceedings of the 3rd International Workshop on Digital Mammography, Chicago, 9-12 June 1996. Amsterdam: Elsevier, 1996.

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Nico, Karssemeijer, and International Workshop on Digital Mammography (4th : 1998 : Nijmegen, Netherlands), eds. Digital mammography: Nijmegen, 1998. Dordrecht: Kluwer Academic Publishers, 1998.

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Radiological Society of North America. Scientific Assembly. 2003 syllabus: Advances in digital radiography : categorical course in diagnostic radiology physics. Edited by Samei Ehsan and Flynn Michael J. PhD. Oak Brook, IL: Radiological Society of North America, 2003.

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G, Gale Alastair, ed. Digital mammography: Proceedings of the 2nd International Workshop on Digital Mammography, York, England, 10-12 July 1994. Amsterdam: Elsevier, 1994.

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Digital forensics for the health sciences: Applications in practice and research. Hershey, PA: Medical Information Science Reference, 2011.

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1945-, Peitgen Heinz-Otto, ed. Digital mammography: IWDM 2002 : 6th International Workshop on Digital Mammography : proceedings of the workshop June 22-25, 2002, Bremen, Germany. Berlin: Springer, 2003.

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Radiography in the digital age: Physics, exposure, radiation biology. Springfield, Ill: Charles C. Thomas, 2011.

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Book chapters on the topic "Radiography, Medical – Digital techniques"

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Bellazzini, R., A. Brez, A. Guerra, M. M. Massai, and M. R. Torquati. "Digital Radiography Using the Individual Photon Counting Technique." In Physics and Engineering of Medical Imaging, 197–204. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3537-2_12.

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Zhao, Liang, Zhigang Peng, Klaus Finkler, Anna Jerebko, Jason J. Corso, and Xiang Zhou. "Automatic Collimation Detection in Digital Radiographs with the Directed Hough Transform and Learning-Based Edge Detection." In Patch-Based Techniques in Medical Imaging, 71–78. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-28194-0_9.

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Seeram, Euclid. "Medical Imaging Informatics." In Digital Radiography, 85–95. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6522-9_10.

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Riederer, S. J., and S. J. Riederer. "Temporal Integration Processing Techniques." In Digital Radiography, 35–53. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-5068-2_3.

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Heuser, Lothar. "Digital Radiography." In Springer Handbook of Medical Technology, 291–310. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-74658-4_15.

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Seeram, Euclid. "Medical Imaging Informatics: An Overview." In Digital Radiography, 165–83. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3244-9_10.

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Ng, Kwan Hoong, Jeannie Hsiu Ding Wong, and Geoffrey D. Clarke. "Digital Radiography." In Problems and Solutions in Medical Physics, 31–39. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2018]- | Series: Series in medical physics and biomedical engineering: CRC Press, 2018. http://dx.doi.org/10.1201/9781351006781-4.

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Kruger, R. A. "Recursive Filtering Techniques Applied to Digital Subtraction Angiography." In Digital Radiography, 133–43. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4684-5068-2_6.

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Rinkel, Jean, and Jean-Marc Dinten. "Quantitative Digital Radiography Image Processing." In Photon-Based Medical Imagery, 123–60. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118601242.ch3.

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Kruger, Robert A. "Current Status of Digital Radiography." In Physics and Engineering of Medical Imaging, 97–109. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3537-2_6.

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Conference papers on the topic "Radiography, Medical – Digital techniques"

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Boone, John M., and James A. Seibert. "Neural network scatter correction technique for digital radiography." In Medical Imaging '90, Newport Beach, 4-9 Feb 90, edited by Roger H. Schneider. SPIE, 1990. http://dx.doi.org/10.1117/12.18827.

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Yun, Seungman, Jaehyuk Kim, Yoonsuk Huh, Jungha Kim, Sujin Park, Jungmin Kim, Jongpil Kim, Kyung Hun Yoon, and JaeMoon Jo. "Theoretical characterization of performance effectiveness of photon-counting technique for digital radiography applications." In SPIE Medical Imaging, edited by Thomas G. Flohr, Joseph Y. Lo, and Taly Gilat Schmidt. SPIE, 2017. http://dx.doi.org/10.1117/12.2254271.

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Huda, Walter, Kent M. Ogden, Ernest M. Scalzetti, Eric F. Dudley, and David R. Dance. "How do radiographic techniques affect mass lesion detection performance in digital mammography?" In Medical Imaging 2004, edited by Dev P. Chakraborty and Miguel P. Eckstein. SPIE, 2004. http://dx.doi.org/10.1117/12.535672.

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Flynn, Michael J., Charles Dodge, Donald J. Peck, and Ann Swinford. "Optimal radiographic techniques for digital mammograms obtained with an amorphous selenium detector." In Medical Imaging 2003, edited by Martin J. Yaffe and Larry E. Antonuk. SPIE, 2003. http://dx.doi.org/10.1117/12.480486.

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Lai, Chao-Jen, Chris C. Shaw, Xinming Liu, Lingyun Chen, Tao Han, and Tianpeng Wang. "Comparison of the performances between anti-scatter grid and slot scanning technique for digital chest radiography: effect of anatomical background." In Medical Imaging, edited by Jiang Hsieh and Ehsan Samei. SPIE, 2008. http://dx.doi.org/10.1117/12.771687.

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Peterzol, Angela, Bruno Bader, Julien Banchet, Claire Caperaa, and Vivian Didier. "Image Quality Assessment of Four Different Computed Radiography Systems for NDT Applications." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97704.

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Computed radiography (CR) is a digital radiographic technique, which uses very similar equipment to conventional radiography except that in place of a film to create the latent image, an imaging plate (IP) made of a photostimulable phosphor is used [1]. CR systems are commonly used in medical applications since they have proven reliability over more than two decades. Conversely, the NDT community has discussed the efficacy of film replacement by CR for more than 15 years. Though some standards were introduced in 2005 (ASTM E 2033, CEN EN 14784-2) and others are on the way (PR ISO 17636-2), CR is actually not included within the French RCCM, while the technique is commonly used in US for nuclear applications according to ASME (Section V, article 2). Since 2006, AREVA has been evaluating the performance of CR in comparison to conventional RT in the framework of EN 14784 for the digital part and the RCCM for the conventional part. The objective was to build a technical justification report to eventually support introduction of CR into the RCCM. In 2009 the subject gave rise to collaboration between AREVA NP – NETEC and EDF-CEIDRE, for a joint project to establish performance limits of CR towards EN 14784 specifications and RCCM image quality indicator (IQI) requirements [2]. In this paper, we present performance comparison results of four different CR systems. The measurements were conducted in 2012 and they demonstrate the current state of achievable image quality in CR. The performance has been evaluated for steel with a thickness range of 20÷60 mm using an Iridium 192 gamma source. Image quality has been assessed in terms of EN 462 and ASTM (E 747, E 1742) IQI. The results have been scored considering the PR ISO 17636-2, RCCM 2007, and ASME V-2010. This also permitted comparison among the different standard requirements.
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Geluk, Ronald J. "Digital equalization radiography." In Medical Imaging '99, edited by John M. Boone and James T. Dobbins III. SPIE, 1999. http://dx.doi.org/10.1117/12.349524.

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Ravin, Carl E. "Digital Radiography and PACS." In 1989 Medical Imaging, edited by Samuel J. Dwyer III, R. Gilbert Jost, and Roger H. Schneider. SPIE, 1989. http://dx.doi.org/10.1117/12.953349.

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Sajewicz, Anthony M., Walter Huda, Denis Hseuh, Kent M. Ogden, Ernest M. Scalzetti, and David R. Dance. "Observer performance and radiographic technique factors in digital mammography." In Medical Imaging 2002, edited by Dev P. Chakraborty and Elizabeth A. Krupinski. SPIE, 2002. http://dx.doi.org/10.1117/12.462668.

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Huda, Walter, Guoying Qu, Zhenxue Jing, Barbara G. Steinbach, and Janice C. Honeyman-Buck. "Radiographic technique factors and imaging performance in digital mammography." In Medical Imaging 2000, edited by James T. Dobbins III and John M. Boone. SPIE, 2000. http://dx.doi.org/10.1117/12.384532.

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Reports on the topic "Radiography, Medical – Digital techniques"

1

Liu, C. T., Lee M. Klynn, and Jay D. Thompson. Monitoring Microstructural Evolution and Crack Formation in a Solid Propellant under Incremental Strain Condition- Using Digital Radiography X-Ray Techniques. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada423473.

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Rudd, Ian. Leveraging Artificial Intelligence and Robotics to Improve Mental Health. Intellectual Archive, July 2022. http://dx.doi.org/10.32370/iaj.2710.

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Artificial Intelligence (AI) is one of the oldest fields of computer science used in building structures that look like human beings in terms of thinking, learning, solving problems, and decision making (Jovanovic et al., 2021). AI technologies and techniques have been in application in various aspects to aid in solving problems and performing tasks more reliably, efficiently, and effectively than what would happen without their use. These technologies have also been reshaping the health sector's field, particularly digital tools and medical robotics (Dantas & Nogaroli, 2021). The new reality has been feasible since there has been exponential growth in the patient health data collected globally. The different technological approaches are revolutionizing medical sciences into dataintensive sciences (Dantas & Nogaroli, 2021). Notably, with digitizing medical records supported the increasing cloud storage, the health sector created a vast and potentially immeasurable volume of biomedical data necessary for implementing robotics and AI. Despite the notable use of AI in healthcare sectors such as dermatology and radiology, its use in psychological healthcare has neem models. Considering the increased mortality and morbidity levels among patients with psychiatric illnesses and the debilitating shortage of psychological healthcare workers, there is a vital requirement for AI and robotics to help in identifying high-risk persons and providing measures that avert and treat mental disorders (Lee et al., 2021). This discussion is focused on understanding how AI and robotics could be employed in improving mental health in the human community. The continued success of this technology in other healthcare fields demonstrates that it could also be used in redefining mental sicknesses objectively, identifying them at a prodromal phase, personalizing the treatments, and empowering patients in their care programs.
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