Relevant bibliographies by topics / Computer aided diagnosis tools

Contents

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

Academic literature on the topic 'Computer aided diagnosis tools'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Computer aided diagnosis tools"

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Colombi, Davide, Maurizio Marvisi, Sara Ramponi, et al. "Computer-Aided Evaluation of Interstitial Lung Diseases." Diagnostics 15, no. 7 (2025): 943. https://doi.org/10.3390/diagnostics15070943.

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The approach for the diagnosis and treatment of interstitial lung diseases (ILDs) has changed in recent years, mainly for the identification of new entities, such as interstitial lung abnormalities (ILAs) and progressive pulmonary fibrosis (PPF). Clinicians and radiologists are facing new challenges for the screening, diagnosis, prognosis, and follow-up of ILDs. The detection and classification of ILAs or the identification of fibrosis progression at high-resolution computed tomography (HRCT) is difficult, with high inter-reader variability, particularly for non-expert radiologists. In the las
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Mun, Seong K., and Dow-Mu Koh. "Special Issue: “Machine Learning for Computer-Aided Diagnosis in Biomedical Imaging”." Diagnostics 12, no. 6 (2022): 1331. http://dx.doi.org/10.3390/diagnostics12061331.

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The radiology imaging community has been developing computer-aided diagnosis (CAD) tools since the early 1990s before the imagination of artificial intelligence (AI) fueled many unbound healthcare expectations and other industries [...]
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Ioanovici, Andrei-Constantin, Andrei-Marian Feier, Ioan Țilea, and Daniela Dobru. "Computer-Aided Diagnosis in Colorectal Cancer: Current Concepts and Future Prospects." Journal of Interdisciplinary Medicine 2, no. 3 (2017): 245–49. http://dx.doi.org/10.1515/jim-2017-0057.

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Abstract Colorectal cancer is an important health issue, both in terms of the number of people affected and the associated costs. Colonoscopy is an important screening method that has a positive impact on the survival of patients with colorectal cancer. The association of colonoscopy with computer-aided diagnostic tools is currently under researchers’ focus, as various methods have already been proposed and show great potential for a better management of this disease. We performed a review of the literature and present a series of aspects, such as the basics of machine learning algorithms, dif
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Molino, F., D. Furia, F. Bar, S. Battista, N. Cappello, and G. Molino. "Computer-Aided Diagnosis in Jaundice: Comparison of Knowledge-based and Probabilistic Approaches." Methods of Information in Medicine 35, no. 01 (1996): 41–51. http://dx.doi.org/10.1055/s-0038-1634634.

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AbstractThe study reported in this paper is aimed at evaluating the effectiveness of a knowledge-based expert system (ICTERUS) in diagnosing jaundiced patients, compared with a statistical system based on probabilistic concepts (TRIAL). The performances of both systems have been evaluated using the same set of data in the same number of patients. Both systems are spin-off products of the European project Euricterus, an EC-COMACBME Project designed to document the occurrence and diagnostic value of clinical findings in the clinical presentation of jaundice in Europe, and have been developed as
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Lorenzo-Ramírez, Marlene Alejandra, Valeria Michelle Pérez-Alvarado, Fermín Paúl Ramírez-Villavicencio, Jesse Sánchez-Cárdenas, Alma Teresa Orozco-Padilla, and Gener J. Avilés-Rodríguez. "Computer aided diagnosis in mammograms for breast cancer screening." Revista de la Facultad de Medicina Humana 24, no. 4 (2024): 159–79. http://dx.doi.org/10.25176/rfmh.v24i4.6554.

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Securing access to quality healthcare services, particularly for essential screening tests like mammograms, presents a significant challenge in developing nations. Women often encounter extensive waiting periods, sometimes extending for several months, to undergo a mammogram. This crucial test plays a pivotal role in the early detection of breast cancer, where timely diagnosis is crucial for effective treatment and enhanced survival prospects. Delays in obtaining a diagnosis can significantly impact the health of patients and their well-being, underscoring the importance of early detection. Co
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Bartolini, Ilaria, and Andrea Di Luzio. "CAT-CAD: A Computer-Aided Diagnosis Tool for Cataplexy." Computers 10, no. 4 (2021): 51. http://dx.doi.org/10.3390/computers10040051.

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Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). A recent approach for the diagnosis of the disease is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists, looking for specific facial behavior motor phenomena. We present here the CAT-CAD tool for automatic detection of cataplexy symptoms, with the double aim of (1) supporting neurologists in the diagnosis/monitoring of the disease and (2) facil
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Jiménez-Gaona, Yuliana, María José Rodríguez-Álvarez, and Vasudevan Lakshminarayanan. "Deep-Learning-Based Computer-Aided Systems for Breast Cancer Imaging: A Critical Review." Applied Sciences 10, no. 22 (2020): 8298. http://dx.doi.org/10.3390/app10228298.

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This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis/detection (CAD) systems, which make use of new deep learning methods to automatically recognize breast images and improve the accuracy of diagnoses made by radiologists. This review is based upon published literature in the past decade (January 2010–January 2020), where we obtained around 250 research articles, and after an eligibility process, 59 articles were presented in more de
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Lee, Juhun, Robert M. Nishikawa, Ingrid Reiser, and John M. Boone. "Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT." Medical Physics 44, no. 5 (2017): 1846–56. http://dx.doi.org/10.1002/mp.12214.

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Ribeiro, Ricardo T., Rui Tato Marinho, and J. Miguel Sanches. "An Ultrasound-Based Computer-Aided Diagnosis Tool for Steatosis Detection." IEEE Journal of Biomedical and Health Informatics 18, no. 4 (2014): 1397–403. http://dx.doi.org/10.1109/jbhi.2013.2284785.

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Chandrasekar, Devadharshini, Dr Burnice Nalina Kumari, and Nikita Ravi et. al. "Revolutionizing Periodontics: The Impact of Digitalization on Diagnosis and Treatment." International Journal of Healthcare and Medical Sciences, no. 103 (September 15, 2024): 33–36. http://dx.doi.org/10.32861/ijhms.103.33.36.

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The objective of this review is to explore the impact of digitalization on periodontics, with a particular focus on its role in enhancing both diagnosis and treatment. Drawing from a range of recent technological advancements, the study reviews the implementation of advanced imaging techniques and artificial intelligence (AI) in clinical practice. Key digital tools such as cone-beam computed tomography (CBCT), digital intraoral scanners, computer-aided design and manufacturing (CAD/CAM), and 3D printing are examined for their contributions to the field. The results indicate that the integratio
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Dissertations / Theses on the topic "Computer aided diagnosis tools"

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Hoh, See Min. "Condition monitoring and fault diagnosis for CNC machine tools." Thesis, Cardiff University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295120.

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Coxon, Andrew. "Computer aided analysis of paraspinal electromyography." Thesis, Teesside University, 2013. http://hdl.handle.net/10149/301616.

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Back pain is responsible for British employees taking 5 million sick days per year. Low back pain (LBP) has a controversial aetiology, with 95% of cases caused by mechanical, non-pathological causes. Current medical treatment for mechanical LBP is an exercise regime designed to restore lumbar stability. Unfortunately this is often a painful process, and therefore difficult to complete. Electromyography (EMG) variables have been shown to be able to discriminate between subjects with and without mechanical LBP. If these variables could be shown to have discriminatory abilities before the actual
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Luther, Ilse. "Semen characteristics of free-ranging African elephants (Loxodonta africana) and Southern white rhinoceros (Ceratotherium simum simum) using Computer-aided sperm analysis, Electron microscopy and Genomics as diagnostic tools." University of the Western Cape, 2016. http://hdl.handle.net/11394/5443.

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Philosophiae Doctor - PhD<br>The survival of free-ranging (in situ) African elephant and Southern white rhinoceros populations are currently being challenged on a daily basis in Africa. Reproductive health is considered a vital component of species conservation. Conservation of the last mega land mammals may ultimately require intervention by breeding management or combined with assisted reproductive technologies (ART). There is a strong case for gathering baseline information, both physiological and biological, of any species, as opportunities arise. During this study a total number of 21 ej
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Borelli, João Eduardo. "Diagnóstico do estado de desgaste de ferramentas para o monitoramento de condições de usinagem de alto desempenho." Universidade de São Paulo, 2000. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-14112017-104229/.

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Durante o processo de usinagem, o conhecimento da temperatura é um dos fatores mais importante na análise do estado da ferramenta. Permite o controle dos fatores mais importantes que influenciam, no uso, na vida e no desgaste da ferramenta. A temperatura na região de contato entre a peça e a ferramenta é resultante do processo de remoção de material durante a operação de corte e é difícil de se obter uma vez que, ou a peça, ou a ferramenta estão em movimento. Uma maneira de se medir a temperatura nessa situação é detectando a radiação de infravermelho. Este trabalho tem objetivo de apresentar
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Elter, Matthias. "Computer-aided diagnosis of breast cancer." Tönning Lübeck Marburg Der Andere-Verl, 2010. http://d-nb.info/1001110773/04.

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Nakamura, Yoshihiko, Takayuki Kitasaka, Kensaku Mori, and Yasuhito Suenaga. "COMPUTER AIDED DIAGNOSIS FOR ABDOMINAL SURGICAL PLANNING." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2006. http://hdl.handle.net/2237/10470.

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Malone, John Philip. "Computer-aided diagnosis of diffuse lung disease." Thesis, University of Bristol, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440143.

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Tembey, Mugdha. "Computer-Aided Diagnosis for Mammographic Microcalcification Clusters." [Tampa, Fla.] : University of South Florida, 2003. http://purl.fcla.edu/fcla/etd/SFE0000168.

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PUTZU, LORENZO. "Computer aided diagnosis algorithms for digital microscopy." Doctoral thesis, Università degli Studi di Cagliari, 2016. http://hdl.handle.net/11584/266877.

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Automatic analysis and information extraction from an image is still a highly chal- lenging research problem in the computer vision area, attempting to describe the image content with computational and mathematical techniques. Moreover the in- formation extracted from the image should be meaningful and as most discrimi- natory as possible, since it will be used to categorize its content according to the analysed problem. In the Medical Imaging domain this issue is even more felt because many important decisions that affect the patient care, depend on the use- fulness of the information
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Mori, Kensaku. "Advances in Computer Aided Diagnosis and Computer Assisted Surgery." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2004. http://hdl.handle.net/2237/10452.

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Books on the topic "Computer aided diagnosis tools"

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Elseid, Arwa Ahmed Gasm, and Alnazier Osman Mohammed Hamza. Computer-Aided Glaucoma Diagnosis System. CRC Press, 2020. http://dx.doi.org/10.1201/9780367406288.

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Das, Rik, Sudarshan Nandy, and Siddhartha Bhattacharyya. Disruptive Trends in Computer Aided Diagnosis. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003045816.

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Su, Ruidan, and Han Liu, eds. Medical Imaging and Computer-Aided Diagnosis. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5199-4.

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Hastie, Trevor. Computer-aided diagnosis of mammographic masses. University of Toronto, Dept. of Statistics, 1996.

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Su, Ruidan, Yudong Zhang, Han Liu, and Alejandro F Frangi, eds. Medical Imaging and Computer-Aided Diagnosis. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-16-6775-6.

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Cook, Ian Ainsworth. Computer aided evaluation of early neoplasms. s.n.], 1987.

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Krishnamoorthy, C. S. Computer aided design: Software and analytical tools. Narosa Pub. House, 1991.

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Krishnamoorthy, C. S. Computer aided design: Software and analytical tools. Springer-Verlag, 1992.

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G, Russell, and Institution of Electrical Engineers, eds. Computer aided tools for VLSI system design. P. Peregrinus Ltd. on behalf of the Institution of Electrical Engineers, 1987.

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Guo, Shuli, Xiaowei Song, and Lina Han. Computer-Aided Intelligent Diagnosis of Skin Melanoma. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-6135-0.

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Book chapters on the topic "Computer aided diagnosis tools"

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Katis, Andreas, Anastasia Mavridou, Dimitra Giannakopoulou, Thomas Pressburger, and Johann Schumann. "Capture, Analyze, Diagnose: Realizability Checking Of Requirements in FRET." In Computer Aided Verification. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13188-2_24.

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AbstractRequirements formalization has become increasingly popular in industrial settings as an effort to disambiguate designs and optimize development time and costs for critical system components. Formal requirements elicitation also enables the employment of analysis tools to prove important properties, such as consistency and realizability. In this paper, we present the realizability analysis framework that we developed as part of the Formal Requirements Elicitation Tool (FRET). Our framework prioritizes usability, and employs state-of-the-art analysis algorithms that support infinite theo
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Mori, Kazuo. "Case Example 6: In-process diagnosis of tool failures in milling." In Computer-aided Maintenance. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5305-2_17.

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Gernert, Regine, and Peter John. "Design of Competence Promoting Multi-Agent-Systems to Support the User in Fault Diagnosis of CNC-Machine Tools." In Computer Aided Systems Theory - EUROCAST’99. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10720123_17.

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Kvak, Daniel, Eva Březinová, Marek Biroš, and Robert Hrubý. "Synthetic Data as a Tool to Combat Racial Bias in Medical AI: Utilizing Generative Models for Optimizing Early Detection of Melanoma in Fitzpatrick Skin Types IV–VI." In Medical Imaging and Computer-Aided Diagnosis. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-16-6775-6_26.

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Abate, Alessandro, Mirco Giacobbe, and Yannik Schnitzer. "Bisimulation Learning." In Computer Aided Verification. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65633-0_8.

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AbstractWe introduce a data-driven approach to computing finite bisimulations for state transition systems with very large, possibly infinite state space. Our novel technique computes stutter-insensitive bisimulations of deterministic systems, which we characterize as the problem of learning a state classifier together with a ranking function for each class. Our procedure learns a candidate state classifier and candidate ranking functions from a finite dataset of sample states; then, it checks whether these generalise to the entire state space using satisfiability modulo theory solving. Upon t
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Singh, Vedpal, Irraivan Elamvazuthi, Varun Jeoti, John George, Norashikin Yahya, and Dileep Kumar. "Ultrasound Based Three Dimensional Computer Aided Diagnosis (CAD) Tool for the Diagnosis of Anterior Talofibular Ligament." In Medical Imaging in Clinical Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33793-7_10.

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Heinonen, T., T. Arola, A. Kalliokoski, et al. "Computer Aided Diagnosis Tool for the Segmentation and Texture Analysis of Medical Images." In IFMBE Proceedings. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03879-2_77.

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Banerjee, Neha, Rachana Sathish, and Debdoot Sheet. "Deep Neural Architecture for Localization and Tracking of Surgical Tools in Cataract Surgery." In Computer Aided Intervention and Diagnostics in Clinical and Medical Images. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04061-1_4.

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Pirovano, Antoine, Hippolyte Heuberger, Sylvain Berlemont, Saïd Ladjal, and Isabelle Bloch. "Improving Interpretability for Computer-Aided Diagnosis Tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-Based Explanations." In Interpretable and Annotation-Efficient Learning for Medical Image Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61166-8_5.

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Pancerz, Krzysztof, Olga Mich, Andrzej Burda, and Jerzy Gomuła. "A Tool for Computer-Aided Diagnosis of Psychological Disorders Based on the MMPI Test: An Overview." In Studies in Computational Intelligence. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19147-8_12.

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Conference papers on the topic "Computer aided diagnosis tools"

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Tran, Nicole, Anisa V. Prasad, Yan Zhuang, et al. "Benchmarking multiorgan segmentation tools for multiparametric T1-weighted abdominal MRI." In Computer-Aided Diagnosis, edited by Susan M. Astley and Axel Wismüller. SPIE, 2025. https://doi.org/10.1117/12.3048938.

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Devnath, Liton, Ian Janzen, Stephen Lam, Ren Yuan, and Calum MacAulay. "Predicting future lung cancer risk in low-dose CT screening patients with AI tools." In Computer-Aided Diagnosis, edited by Susan M. Astley and Axel Wismüller. SPIE, 2025. https://doi.org/10.1117/12.3045828.

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Zhuang, Yan, Abhinav Suri, Tejas Sudharshan Mathai, Brandon Khoury, and Ronald M. Summers. "A fully automated pancreatic subregion segmentation tool for CT." In Computer-Aided Diagnosis, edited by Susan M. Astley and Axel Wismüller. SPIE, 2025. https://doi.org/10.1117/12.3047889.

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Lee, Andrew, Robert B. Parker, Sarah Poon, Dan Gunter, Alexander W. Dowling, and Bethany Nicholson. "Model Diagnostics for Equation-Oriented Models: Roadblocks and the Path Forward." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.147875.

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Equation-Oriented (EO) modeling techniques have been gaining popularity as an alternative for simulating and optimizing process systems due to their flexibility and ability to leverage state-of-the-art solvers inaccessible to many procedural modeling approaches. Despite these advantages, adopting EO modeling tools remains challenging due to the significant learning curve and effort required to build and solve models. Many techniques are available to help diagnose problems with EO process models and reduce the effort required to create and use them. However, these techniques still need to be in
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Allan, Douglas A., Anca Ostace, Andrew Lee, et al. "Jacobian-based Model Diagnostics and Application to Equation Oriented Modeling of a Carbon Capture System." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.160262.

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Equation-oriented (EO) modeling has the potential to enable the effective design and optimization of the operation of advanced energy systems. However, advanced modeling of energy systems results in a large number of variables and non-linear equations, and it can be difficult to search through these to identify the culprit(s) responsible for convergence issues. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms so t
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Fathallah, Wyssem, Hiba Mzoughi, Sawsan Selmi, Abdelbaki Souid, and Hedi Sakli. "Computer Aided Diagnosis CAD tool for lung and thoracic pathologies detection from chest X-ray images." In 2025 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2025. https://doi.org/10.1109/iwcmc65282.2025.11059573.

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Bento, Mariana P., Roberto M. Souza, Richard Frayne, and Marina Salluzzi. "Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol." In Computer-Aided Diagnosis, edited by Horst K. Hahn and Kensaku Mori. SPIE, 2019. http://dx.doi.org/10.1117/12.2512819.

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Guan, Shuyue, Ravi K. Samala, Arian Arab, and Weijie Chen. "MISS-tool: medical image segmentation synthesis tool to emulate segmentation errors." In Computer-Aided Diagnosis, edited by Khan M. Iftekharuddin and Weijie Chen. SPIE, 2023. http://dx.doi.org/10.1117/12.2653650.

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Vandewiele, Stijn, Jonas De Vylder, Bart Diricx, Edward Sandra, and Tom Kimpe. "Open-source tool for model performance analysis for subpopulations." In Computer-Aided Diagnosis, edited by Khan M. Iftekharuddin and Weijie Chen. SPIE, 2023. http://dx.doi.org/10.1117/12.2653453.

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Burgon, Alexis, Nicholas Petrick, Berkman Sahiner, Gene Pennello, Kenny Cha, and Ravi K. Samala. "A tool for the assessment of AI generalizability via decision space composition." In Computer-Aided Diagnosis, edited by Susan M. Astley and Weijie Chen. SPIE, 2024. http://dx.doi.org/10.1117/12.3008580.

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Reports on the topic "Computer aided diagnosis tools"

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Floyd, Carey E. Computer Aided Breast Cancer Diagnosis. Defense Technical Information Center, 1996. http://dx.doi.org/10.21236/ada325798.

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Floyd, Carey E. Computer Aided Breast Cancer Diagnosis. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada392958.

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Floyd, Carey E. Computer Aided Breast Cancer Diagnosis. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada383108.

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Jiang, Yulei. Computer-Aided Diagnosis of Digital Mammograms. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada396524.

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Jiang, Yulei. Computer-Aided Diagnosis of Digital Mammograms. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada431258.

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Jiang, Yulei. Computer-Aided Diagnosis of Breast Lesions. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada410986.

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Jiang, Yulei. Computer-Aided Diagnosis of Digital Mammograms. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada421590.

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Kupinski, Matthew A. Investigation of Genetic Algorithms for Computer-Aided Diagnosis. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada393995.

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Chan, Heang P. Digital Mammography: Advanced Computer-Aided Breast Cancer Diagnosis. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada420159.

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Kupinski, Matthew A. Investigation of Genetic Algorithms for Computer-Aided Diagnosis. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada391457.

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