Journal articles: 'DICOM'

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Hackländer, Thomas, Klaus Kleber, Jens Martin, and Heinrich Mertens. "DICOM router." Academic Radiology 12, no. 3 (March 2005): 385–92. http://dx.doi.org/10.1016/j.acra.2004.11.015.

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D’Addazio, Gianmaria, Edit Xhajanka, Tonino Traini, Manlio Santilli, Imena Rexhepi, Giovanna Murmura, Sergio Caputi, and Bruna Sinjari. "Accuracy of DICOM–DICOM vs. DICOM–STL Protocols in Computer-Guided Surgery: A Human Clinical Study." Journal of Clinical Medicine 11, no. 9 (April 22, 2022): 2336. http://dx.doi.org/10.3390/jcm11092336.

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Guided implant surgery can enhance implant placement positioning, increasing predictability and decreasing postoperative complications., To date, the best protocol to be used for template realization is still unknown. Thus, the aim herein was to clinically compare the accuracy of two different protocols. A total of 48 implants were divided into Group A (24 implants), in which a stereolithographic template was realized using the digital imaging and communications in medicine (DICOM) data arrived from cone beam computer tomographies (CBCTs) (patients and prothesis alone), and Group B (24 implant), in which a standard intraoral stent with a standardized extraoral support was used for patients’ intraoral impressions and CBCT. The preimplant virtual planning and postsurgery CBCT images of both groups were superimposed, and differences were registered in terms of average deviations at the platform (a) and implant apex (b), mean depth change (c), and angular deviation (d). The results demonstrated that there were no statistically significant differences between groups (p = 0.76) for the parameters measured. However, statistically significant differences (p < 0.05) were found between maxillary and mandible implant surgery, as the latter showed greater accuracy. Additional studies are necessary to further reduce discrepancies between planning and surgical procedures.

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Caffery, Liam J. "The Role of Standards in Accelerating the Uptake of Artificial Intelligence in Dermatology." Iproceedings 8, no. 1 (February 23, 2022): e36890. http://dx.doi.org/10.2196/36890.

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Background The use of artificial intelligence (AI) for dermatology is showing great promise in research contexts. However, the clinical use of AI in dermatology is still limited. The uptake of medical imaging standards for dermatology imaging is also limited. Standards adoption is more widespread in other imaging specialties (eg, radiology) as is the clinical use of AI. Digital Image Communication in Medicine (DICOM) is the standard for medical imaging. DICOM standardizes image formats and associated metadata. Further, DICOM facilitates interoperability between actors in the digital health ecosystem. Objective This study aimed to identify how medical imaging standards, in particular DICOM, can support the clinical use of AI. Methods Design Science Research Methodology was used to determine the role of DICOM in AI-based medical imaging workflows. Scenarios were identified and synthesized using expert consensus. Results The key benefits of using DICOM to improve the clinical use of AI were the potential to encode artefacts derived from the AI process as DICOM objects and store them alongside the original images. Such objects include downsized or down-sampled images, segmentation objects, or visual explainability maps (eg, class activation maps). DICOM can facilitate interoperability between actors in the medical imaging workflow pipeline and permits the inclusion of AI evidence creators in this pipeline. Owing to standardized image formats and metadata, DICOM can be beneficial for the curation of multi-institutional data sets. The key challenge of using DICOM is limited uptake in some specialties including dermatology. Conclusions DICOM offers potential to accelerate the clinical adoption of AI in dermatology by addressing several technological issues. More widespread uptake of DICOM in dermatology imaging is required to achieve this potential. Conflicts of Interest None declared.

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Varma, DanduRavi. "Free DICOM browsers." Indian Journal of Radiology and Imaging 18, no. 1 (2008): 12. http://dx.doi.org/10.4103/0971-3026.38503.

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Lefèvre, Jean-Éric. "DICOM, Mode d’emploi." RBM-News 20, no. 10 (December 1998): 8–12. http://dx.doi.org/10.1016/s0222-0776(00)89016-1.

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Lefèvre, Jean-Éric. "DICOM, mode d'emploi." RBM-News 21, no. 1 (March 1999): 9–12. http://dx.doi.org/10.1016/s0222-0776(99)89005-1.

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Parisot, Charles. "The DICOM standard." International Journal of Cardiac Imaging 11, no. 3 (September 1995): 171–77. http://dx.doi.org/10.1007/bf01143137.

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Hussein, Rada, Uwe Engelmann, Andre Schroeter, and Hans-Peter Meinzer. "DICOM Structured Reporting." RadioGraphics 24, no. 3 (May 2004): 891–96. http://dx.doi.org/10.1148/rg.243035710.

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Hussein, Rada, Uwe Engelmann, Andre Schroeter, and Hans-Peter Meinzer. "DICOM Structured Reporting." RadioGraphics 24, no. 3 (May 2004): 897–909. http://dx.doi.org/10.1148/rg.243035722.

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Estrela, Vania V. "DICOM’s Standardization in Histo-Pathology." Medical Technologies Journal 4, no. 3 (December 7, 2020): 578–79. http://dx.doi.org/10.26415/2572-004x-vol4iss3p578-579.

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Background: The Digital Imaging and Communications in Medicine (DICOM) standard helps to represent, store, and to exchange healthcare images associated with its data. DICOM develops over time and is continuously adapted to match the rigors of new clinical demands and technologies. An uphill battle in this regard is to conciliate new software programs with legacy systems. Methods: This work discusses the essential aspects of the standard and assesses its capabilities and limitations in a multisite, multivendor healthcare system aiming at Whole Slicing Image (WSI) procedures. Selected relevant DICOM attributes help to develop and organize WSI applications that extract and handle image data, integrated patient records, and metadata. DICOM must also interface with proprietary file formats, clinical metadata and from different laboratory information systems. Standard DICOM validation tools to measure encoding, storing, querying and retrieval of medical data can verify the generated DICOM files over the web. Results: This work investigates the current regulations and recommendations for the use of DICOM with WSI data. They rely mostly on the EU guidelines that help envision future needs and extensions based on new examination modalities like concurrent use of WSI with in-vitro imaging and 3D WSI. Conclusion: A DICOM file format and communication protocol for pathology has been defined. However, adoption by vendors and in the field is pending. DICOM allows efficient access and prompt availability of WSI data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology. In the future, the DICOM standard will have to address several issues due to the way samples are gathered and encompassing new imaging technologies.

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Mileva, Aleksandra, Aleksandar Velinov, Vesna Dimitrova, Luca Caviglione, and Steffen Wendzel. "Information Hiding in the DICOM Message Service and Upper Layer Service with Entropy-Based Detection." Entropy 24, no. 2 (January 25, 2022): 176. http://dx.doi.org/10.3390/e24020176.

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The DICOM (Digital Imaging and COmmunication in Medicine) standard provides a framework for a diagnostically-accurate representation, processing, transfer, storage and display of medical imaging data. Information hiding in DICOM is currently limited to the application of digital media steganography and watermarking techniques on the media parts of DICOM files, as well as text steganographic techniques for embedding information in metadata of DICOM files. To improve the overall security of the DICOM standard, we investigate its susceptibility to network steganographic techniques. To this aim, we develop several network covert channels that can be created by using a specific transport mechanism – the DICOM Message Service and Upper Layer Service. The bandwidth, undetectability and robustness of the proposed covert channels are evaluated, and potential countermeasures are suggested. Moreover, a detection mechanism leveraging entropy-based metrics is introduced and its performance has been assessed.

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Miao, Yu, Hua Min Yang, Wei Li Shi, Yan Ni Cao, and Li Yuan Zhang. "Research on Applied Technology in Storing and Transmitting Medical Image Based on DICOM." Advanced Materials Research 1014 (July 2014): 395–98. http://dx.doi.org/10.4028/www.scientific.net/amr.1014.395.

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DICOM is the international standard for the digital imaging communication in medicine. This paper introduces the development of DICOM and analyzes the communication process based on DICOM protocol. Besides, the communication between store SCP and store SCU was designed and implemented.

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Liu, Li Jun, and Qing Song Huang. "CloudDICOM: A Large-Scale Online Storage and Sharing System for DICOM Images." Advanced Materials Research 756-759 (September 2013): 2037–41. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2037.

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Online storage and sharing for large-scale DICOM images becomes increasingly important for medical organizations or large hospitals. This paper presents a distributed architecture based on Hadoop and HBase to support online storage and sharing for DICOM images. An experimental system called CloudDICOM is designed and realized based on this architecture. The paper focuses on designing the architecture, workflow, data schema, and then on analyzing the components in CloudDICOM. Firstly, DICOM messages sent by clients will be received, converted and stored into Hadoop and HBase. Then, these messages will be indexed and generated query and WADO index database. The components of DICOM query and WADO based on this index are implemented to provide online DICOM query and WADO service for clients. The test results demonstrate that CloudDICOM can provide online storage and sharing service for large-scale medical images, and support standard DICOM Query and WADO service.

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Zhang, Menghe, and Jürgen P. Schulze. "Server-Aided 3D DICOM Viewer for Mobile Platforms." Electronic Imaging 2021, no. 13 (January 18, 2021): 179–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.13.ervr-179.

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Digital Imaging and Communications in Medicine (DICOM) is an international standard to transfer, store, retrieve, print, process and display medical imaging information. It provides a standardized method to store medical images from many types of imaging devices. Typically, CT and MRI scans, which are composed of 2D slice images in DICOM format, can be inspected and analyzed with DICOM-compatible imaging software. Additionally, the DICOM format provides important information to assemble cross-sections into 3D volumetric datasets. Not many DICOM viewers are available for mobile platforms (smartphones and tablets), and most of them are 2D-based with limited functionality and user interaction. This paper reports on our efforts to design and implement a volumetric 3D DICOM viewer for mobile devices with real-time rendering, interaction, a full transfer function editor and server access capabilities. 3D DICOM image sets, either loaded from the device or downloaded from a remote server, can be rendered at up to 60 fps on Android devices. By connecting to our server, users can a) get pre-computed image quality metrics and organ segmentation results, and b) share their experience and synchronize views with other users on different platforms.

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Gibaud, B. "La contribution de DICOM : le compte rendu structure (DICOM structured reporting)." Journal de Radiologie 85, no. 9 (September 2004): 1144. http://dx.doi.org/10.1016/s0221-0363(04)76444-6.

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Chabriais, J., and B. Gibaud. "NST3 Le compte rendu structure DICOM (structured reporting ou DICOM SR)." Journal de Radiologie 85, no. 9 (September 2004): 1531. http://dx.doi.org/10.1016/s0221-0363(04)77762-8.

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Burgess, Jeff. "Digital DICOM in Dentistry." Open Dentistry Journal 9, no. 1 (July 31, 2015): 330–36. http://dx.doi.org/10.2174/1874210601509010330.

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Similar to Medicine, digital communication, information processing, and x-ray imaging have changed the face of dentistry. The incorporation of digital systems into medical and dental practice has necessitated development of a standard that allows reliable transmission of information between the devices taking the images, devices storing the images, and devices displaying the images. This standard is termed as DICOM. The following article briefly reviews how DICOM came about, how dentistry is involved, the various elements that are part of the DICOM system, and how DICOM is currently used in dentistry.

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Gideon, Samuel, and Taat Guswantoro. "OPTIMASI CITRA DICOM DENGAN MENGGUNAKAN APLIKASI PADA SMARTPHONE ANDROID." Prosiding SNFA (Seminar Nasional Fisika dan Aplikasinya) 3 (February 28, 2019): 258. http://dx.doi.org/10.20961/prosidingsnfa.v3i0.28558.

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Abstract: A radiographic image is generated from a mapping of attenuation of the X-ray beam that passed through a material. Over the past few years, as computer acquisition technology has grown, conventional diagnostic medical imaging modalities have increasingly been replaced by digital imagery. Computed radiography (CR) is one of radiographic image acquisition using computers. CR images could be either .jpg files or DICOM files. We exposed some wrenches which diameter of 5.68 mm; 3.99 mm and 3.2 mm as well as a bottle and a circular cork. We use Siemens mobile x-ray to expose the objects and DroidRender 3D DICOM Viewer as the DICOM viewer. We got two images which are .jpg file and DICOM file respectively. We adjust WW and WL parameters in order to optimize the image of the DICOM file. The results are WW = 2833 and WC = 2170.Abstrak: Citra medis yang dihasilkan oleh sistem radiografi pada dasarnya adalah pemetaan dari berkas sinar-X yang diteruskan yang dinyatakan melalui hukum penurunan intensitas sinar-X. Selama beberapa tahun terakhir, dengan semakin berkembangnya teknologi akuisisi komputer, modalitas pencitraan medis diagnostik konvensional semakin digantikan oleh citra digital. Computed radiography (CR) merupakan salah satu teknologi akuisisi komputer pengolah citra radiografi. Hasil citra radiografi pada CR dapat berbentuk file .jpg ataupun DICOM. Untuk membaca file DICOM harus digunakan DICOM viewer yang dapat diunduh secara gratis dari internet. Pada penelitian ini, obyek-obyek yang dipapari sinar-X yaitu kunci inggris dengan tebal diameter 5,68 mm; 3,99 mm dan 3,2 mm serta botol dan gabus berbentuk lingkaran. Pesawat sinar-X yang digunakan adalah mobile x-ray bermerk Siemens. Aplikasi DICOM viewer yang digunakan adalah DroidRender 3D DICOM Viewer. Dari hasil eksperimen, pengaturan WW dan WC pada aplikasi untuk dapat menampilkan gabus secara optimal diperoleh pada nilai WW = 2833 dan WC = 2170.

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Shahid, Arsalan, Mehran H. Bazargani, Paul Banahan, Brian Mac Namee, Tahar Kechadi, Ceara Treacy, Gilbert Regan, and Peter MacMahon. "A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis." Healthcare 10, no. 5 (April 19, 2022): 755. http://dx.doi.org/10.3390/healthcare10050755.

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Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients’ Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification process of DICOM attributes, for example, what needs to be considered before removing a DICOM attribute. In this paper, we first highlight and review the key challenges in the medical image data de-identification process. In this paper, we develop a two-stage de-identification process for CT scan images available in DICOM file format. In the first stage of the de-identification process, the patient’s PII—including name, date of birth, etc., are removed at the hospital facility using the export process available in their Picture Archiving and Communication System (PACS). The second stage employs the proposed DICOM de-identification tool for an exhaustive attribute-level investigation to further de-identify and ensure that all PII has been removed. Finally, we provide a roadmap for future considerations to build a semi-automated or automated tool for the DICOM datasets de-identification.

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NISHIHARA, EITARO. "DICOM, Behind the Scene." Japanese Journal of Radiological Technology 57, no. 3 (2001): 253–57. http://dx.doi.org/10.6009/jjrt.kj00001357493.

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Vizza, Patrizia, Giuseppe Lucio Cascini, Rosario Curia, Loredana Sisca, and Filippo Aiello. "Annotation of dicom information." ACM SIGBioinformatics Record 6, no. 2 (August 3, 2016): 1–2. http://dx.doi.org/10.1145/2983313.2983314.

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Chabriais, J., B. Gibaud, F. Aubry, Y. Gandon, G. Mevel, J. Guignot, A. Todd Pokropek, and J. Riesmeier. "NST2 Introduction a DICOM." Journal de Radiologie 85, no. 9 (September 2004): 1531. http://dx.doi.org/10.1016/s0221-0363(04)77761-6.

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Flanders, Adam E., and John A. Carrino. "Understanding DICOM and IHE." Seminars in Roentgenology 38, no. 3 (July 2003): 270–81. http://dx.doi.org/10.1016/s0037-198x(03)00044-0.

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Ackerly, T., M. Geso, and R. Smith. "Radiotherapy DICOM packet sniffing." Australasian Physics & Engineering Sciences in Medicine 31, no. 3 (September 2008): 243–51. http://dx.doi.org/10.1007/bf03179351.

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Farman, Allan G. "Applying DICOM to Dentistry." Journal of Digital Imaging 18, no. 1 (November 25, 2004): 23–27. http://dx.doi.org/10.1007/s10278-004-1029-z.

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Potter, Glenn, Rick Busbridge, Michael Toland, and Paul Nagy. "Mastering DICOM with DVTk." Journal of Digital Imaging 20, S1 (August 7, 2007): 47–62. http://dx.doi.org/10.1007/s10278-007-9057-0.

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Suzuki, Makoto. "DICOM Standards Committee Attendance Report—How DICOM Standards are Developed and Maintained—." Japanese Journal of Radiological Technology 64, no. 5 (2008): 658–61. http://dx.doi.org/10.6009/jjrt.64.658.

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Langer, Steve G. "A Flexible Database Architecture for Mining DICOM Objects: the DICOM Data Warehouse." Journal of Digital Imaging 25, no. 2 (November 12, 2011): 206–12. http://dx.doi.org/10.1007/s10278-011-9434-6.

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Chen, Pei Jiang. "Medical Image Display Based on DICOM." Key Engineering Materials 480-481 (June 2011): 932–37. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.932.

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Modern medical diagnose has higher demand for image archiving and communication, the medical image display technology is mainly studied under the Windows platform. According to the analysis of the DICOM 3.0 standards and file formats, the general idea of the conversion from DICOM format to BMP format is proposed. Based on the object-oriented programming idea, a format conversion class called CDicomConvert is designed by using Visual C++. The class encapsulates many data and methods for DICOM image processing, and the class CDib is also improved. The result of the software running shows that it can convert the DICOM file to BMP format, and the medical image can be displayed under Windows.

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Fedorov, Andriy, David Clunie, Ethan Ulrich, Christian Bauer, Andreas Wahle, Bartley Brown, Michael Onken, et al. "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research." PeerJ 4 (May 24, 2016): e2057. http://dx.doi.org/10.7717/peerj.2057.

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Background.Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM®) international standard and free open-source software.Methods.Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data.Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software.Discussion.We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

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Hazarika, Hirak Jyoti, Akash Handique, and S. Ravikumar S. Ravikumar. "DICOM-based medical image repository using DSpace." Collection and Curation 39, no. 4 (February 20, 2020): 105–15. http://dx.doi.org/10.1108/cc-11-2019-0039.

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Purpose This paper aims to provide image repository to the medical professional in an open source platform, which will increase the visibility of Digital Imaging and Communication in Medicine (DICOM) image in a network mode; further, the proposed system will reduce the storage cost of the images to significant level. Design/methodology/approach The authors have developed a new institutional repository model for the medical professionals cum radiologists to preserve, store and retrieve medical images from one database with the help of open source software. The authors used JavaScript programming to integrate and develop the DICOM Standard with DSpace. Findings Major outcome of this work is that DICOM images can be accommodated in DSpace without modifying the image properties and keeping intact the various dimensions of image viewing options. Further, it was found that the images are retrieved without any ease because of the robust indexing system. Research limitations/implications Major limitation of this study was the size of the data (5000 DICOM image) with which the authors have tested the system. The scalability of the system has to be tested on various fronts, for which separate study has to be done. Practical implications Once this system is in place, DICOM user can store, retrieve and access the image from Web platform. This proposed repository will be the storehouse of various DICOM images with reasonable storage costs. Originality/value In addition to exploring the opportunities of open source software (OSS) implementation in Medical Fields, this study includes issues related to implementation of open source repository for storing and preserving medical image. This is the first time in Library Science field to create and develop Open Source DICOM Medical Image Library with the help of DSpace. The study will create value for library professionals as well as medical professionals and OSS vendors to understand the medical market in the context of OSS.

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Koutelakis, George V., George K. Anastassopoulos, and Dimitrios K. Lymberopoulos. "Application of Multiprotocol Medical Imaging Communications and an Extended DICOM WADO Service in a Teleradiology Architecture." International Journal of Telemedicine and Applications 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/271758.

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Multiprotocol medical imaging communication through the Internet is more flexible than the tight DICOM transfers. This paper introduces a modular multiprotocol teleradiology architecture that integrates DICOM and common Internet services (based on web, FTP, and E-mail) into a unique operational domain. The extended WADO service (a web extension of DICOM) and the other proposed services allow access to all levels of the DICOM information hierarchy as opposed to solely Object level. A lightweight client site is considered adequate, because the server site of the architecture provides clients with service interfaces through the web as well as invulnerable space for temporary storage, called as User Domains, so that users fulfill their applications' tasks. The proposed teleradiology architecture is pilot implemented using mainly Java-based technologies and is evaluated by engineers in collaboration with doctors. The new architecture ensures flexibility in access, user mobility, and enhanced data security.

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Dean Bidgood, W. "The SNOMED DICOM Microglossary: Controlled Terminology Resource for Data Interchange in Biomedical Imaging." Methods of Information in Medicine 37, no. 04/05 (October 1998): 404–14. http://dx.doi.org/10.1055/s-0038-1634557.

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AbstractThis paper describes an authoritative, non-proprietary information resource that provides an efficient mechanism for embedding specialized clinical knowledge into the design of healthcare telecommunications systems. The resource marries two types of data interchange standards, a message/electronic-document standard and a terminology standard. In technical terms, it is part protocol and part database. Industry, academia, professional specialty societies, and the federal government participated in its development. The development of mUlti-specialty content has broadly engaged biomedical domain experts to an unprecedented degree in voluntary, non-proprietary message/document-standards development. The resource is the SNOMED DICOM Microglossary (SDM) [1], a message-terminology (or document-content) mapping resource. The message/electronicdocument standard is DICOM (Digital Imaging and Communications in Medicine) [2]. The terminology standard is SNOMED, (Systematized Nomenclature of Human and Veterinary Medicine) [31. The SDM specifies the mapping of multi-specialty imaging terminology from SNOMED to DICOM data elements. DICOM provides semantic constraints and a framework for discou rse that are lacking in SNOMED. Thus the message standard and the computerbased terminology both depend upon and complete each other. The combination is synergistic. By substitution of different templates of specialty terminology from the SDM, a generic message template, such as the DICOM Visible Light (Color Diagnostic) Image or the DICOM Structured Reporting specification can be reconfigured for diverse applications. Professional societies, with technical assistance from the College of American Pathologists, contribute and maintain their portions of the terminology, and can use SDM templates and term lists in clinical practice guidelines for the structure and content of computer-based patient records.

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Lynes, James, and Chris Riha. "Learning the Fundamentals of…DICOM." Biomedical Instrumentation & Technology 38, no. 1 (January 2004): 35–38. http://dx.doi.org/10.2345/0899-8205(2004)38[35:ltfo]2.0.co;2.

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Trianni, Annalisa. "DICOM standards for patient dosimetry." Physica Medica 32 (September 2016): 188. http://dx.doi.org/10.1016/j.ejmp.2016.07.326.

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Suzuki, Makoto. "DICOM Standards Committee Attendance Report." Japanese Journal of Radiological Technology 64, no. 6 (2008): 766–67. http://dx.doi.org/10.6009/jjrt.64.766.

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Silva, Luís A. Bastião, Carlos Costa, and José Luis Oliveira. "DICOM relay over the cloud." International Journal of Computer Assisted Radiology and Surgery 8, no. 3 (August 9, 2012): 323–33. http://dx.doi.org/10.1007/s11548-012-0785-3.

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Grauer, Dan, Lucia S. H. Cevidanes, and William R. Proffit. "Working with DICOM craniofacial images." American Journal of Orthodontics and Dentofacial Orthopedics 136, no. 3 (September 2009): 460–70. http://dx.doi.org/10.1016/j.ajodo.2009.04.016.

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Yu, Cong, and Zhihong Yao. "XML-Based DICOM Data Format." Journal of Digital Imaging 23, no. 2 (January 28, 2009): 192–202. http://dx.doi.org/10.1007/s10278-008-9173-5.

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Noumeir, Rita, and Jean-François Pambrun. "Teaching DICOM by Problem Solving." Journal of Digital Imaging 25, no. 5 (April 5, 2012): 653–61. http://dx.doi.org/10.1007/s10278-012-9471-9.

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41

Langer, Steve G. "DICOM Data Warehouse: Part 2." Journal of Digital Imaging 29, no. 3 (October 30, 2015): 309–13. http://dx.doi.org/10.1007/s10278-015-9830-4.

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42

Mildenberger, Peter, Marco Eichelberg, and Eric Martin. "Introduction to the DICOM standard." European Radiology 12, no. 4 (September 15, 2001): 920–27. http://dx.doi.org/10.1007/s003300101100.

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Чирко, Р. А., and Н. Р. Урманцева. "Noninvasive Examination Analysis System for Cardiovascular Surgeon / Phlebologist Decision-Making Support." Успехи кибернетики / Russian Journal of Cybernetics, no. 3(11) (September 30, 2022): 42–51. http://dx.doi.org/10.51790/2712-9942-2022-3-3-5.

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в статье рассматривается система анализа результатов неинвазивных исследований пациента для поддержки принятия решений сердечно-сосудистого хирурга-флеболога. Программа будет помогать в принятии решений врачу-флебологу для определения кода классификации CEAP в спорных и сложных случаях путем распознавания загруженного в программу снимка формата DICOM сверточной нейронной сетью.В процессе обучения нейронной сети использовался метод увеличения контрастности черно-белого DICOM-снимка. За счет этого метода нейронная сеть лучше обрабатывает снимок и выводит более точные результаты распознавания. Таким образом, среднее значение процента распознавания варьируется от 86,1 до 97,4 %. this study discusses a system for analyzing noninvasive examination results to support the decision-making by a cardiovascular surgeon/phlebologist. The software helps the phlebologist in making decisions to determine the CEAP classification code in controversial and complicated cases. The system recognizes uploaded DICOM format images with a convolutional neural network.Contrast enhancement of b/w DICOM images was applied for the neural network training. It improves the image handling and increases the recognition accuracy. The average recognition rate is from 86.1 to 97.4 %.

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Savón Berenguer, Asday, and Henry Blanco Lores. "Sistema de Transmisión Interhospitalaria de Imágenes Médicas." Orange Journal 3, no. 6 (January 11, 2022): 48–57. http://dx.doi.org/10.46502/issn.2710-995x/2021.6.05.

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La transmisión de imágenes médicas entre instituciones hospitalarias, basada en estándares modernos y de manera segura, constituye una demanda no satisfecha dentro del Sistema de Salud de Cuba. Particularmente los departamentos radiológicos, que basan sus servicios en sistemas PACS, perciben tanto el incremento de los volúmenes diarios de información médica por las distintas modalidades imagenológicas como la reducción de personal especializado para analizar estos altos volúmenes. Las herramientas informáticas desplegadas en las instituciones hospitalarias no garantizan la compatibilidad con la normativa DICOM para la transmisión de imágenes médicas, lo cual limita o impide el intercambio entre ellas. Se propone una solución basada en el sistema imagis PACS, desplegado en toda la región oriental de Cuba, y los servicios DICOM ofrecidos a través de la web que implementa el servidor DICOM ligero Orthanc, basados en el estándar DICOM. Se diseña un experimento para la validación de la solución, del cual se exponen los resultados obtenidos.

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45

Jozić, Krešimir, Nikolina Frid, Alan Jović, and Željka Mihajlović. "DICOM SIVR: A web architecture and platform for seamless DICOM image and volume rendering." SoftwareX 18 (June 2022): 101063. http://dx.doi.org/10.1016/j.softx.2022.101063.

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46

Friedrich, Kathrin. "Designing Digital Diagnostics." Digital Culture & Society 6, no. 2 (December 1, 2020): 115–32. http://dx.doi.org/10.14361/dcs-2020-0207.

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Abstract Since the 1990s Western clinical radiology has been confronted with a fundamental media-induced change - the so-called analogue-digital migration. Film-based diagnostics and archiving of radiological images are transformed into digital interfaces and infrastructures. Networked software applications, namely picture archiving and communication systems (PACS), provide a new basis for processing and displaying image data. The design and implementation of PACS and their (user) interfaces challenged, amongst others, the search for data standards for digital diagnostics. The data format DICOM (Digital Imaging and Communication) was developed to provide the technological basis for encoding image data. Simultaneously, DICOM determines how patients’ bodies are rendered machine-readable and how radiologists are able to gain software-based insights. A main function of DICOM metadata is encoding and continuously actualising patient identification for technological and human actors. A misidentification of image data and specific patient could lead to fatal errors in the furthe+r treatment process. Accordingly, metadata themselves meander between being invisible to the human user and being essential and hence necessarily visible information for diagnostics. Shifting between normativity and fluidity, DICOM metadata enables new practices of radiological diagnostics, which literally bear vital consequences for patients and, on another level, for the profession of radiology. The paper analyses inherent politics and tensions of metadata from a media theoretical point of view by employing the case of the DICOM standard. Based on subject-specific discourses, data models as well as an in-depth examination of exemplary DICOM metadata it shows how (meta)data politics redefine diagnostic infrastructures and routines as well as gain impact on epistemic and aesthetic practices at the turn of the analogue-digital migration.

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Thiel, A., T. Tolxdorff, and J. Bernarding. "Realization of Security Concepts for DICOM-based Distributed Medical Services." Methods of Information in Medicine 39, no. 04/05 (2000): 348–52. http://dx.doi.org/10.1055/s-0038-1634446.

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Abstract:Exploiting distributed hard- and software resources for tele-medicine requires a fast, secure, and platform-independent data exchange. Standards without inherent security mechanisms such as DICOM may ease non-authorized data access. Therefore, exemplary telemedical data streams were analyzed within the Berlin metropolitan area network using specialized magnetic resonance imaging techniques and distributed resources for data postprocessing. For secure DICOM communication both the Secure Socket Layer Protocol and a DICOM-conform partial encryption of patient-relevant data were implemented. Partial encryption exhibited the highest transfer rate and enabled a secure long-term storage. Different data streams between secured and unsecured networks were realized using partial encryption.

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Reiners, Chr, and M. Laßmann. "A DICOM based PACS for nuclear medicine." Nuklearmedizin 41, no. 01 (2002): 52–60. http://dx.doi.org/10.1055/s-0038-1623993.

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SummaryThe installation of a Radiology Information System (RIS) connected to a Hospital Information System (HIS) and a Picture Archiving and Communications System (PACS) seems mandatory for a nuclear medicine department in order to guarantee a high patient throughput. With these systems a fast transmission of reports, images to the in- and out-patients’ wards and private practitioners is realized. Therefore, since April 2000, at the department of nuclear medicine of the university of Würzburg a completely DICOM based PACS has been implemented in addition to the RIS.With this system a DICOM based workflow is realized throughout the department of nuclear medicine for reporting and archiving.The PACS is connected to six gamma-cameras, a PET scanner, a bone densitometry system and an ultrasound device. The volume of image data archived per month is 4 GByte. Patient demographics are provided to the modalities via DICOM-Worklist. With these PACS components a department specific archive purely based on DICOM can be realized. During the installation process problems occurred mainly because of the complex DICOM standard for nuclear medicine. Related to that is the problem that most of the software implementations still contain bugs or are not adapted to the needs of a nuclear medicine department (particularly for PET).A communication software for the distribution of nuclear medicine reports and images based on techniques used for the worldwide web is currently tested.

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Bernarding, Johannes, Andreas Thiel, and Alexander Grzesik. "A JAVA-based DICOM server with integration of clinical findings and DICOM-conform data encryption." International Journal of Medical Informatics 64, no. 2-3 (December 2001): 429–38. http://dx.doi.org/10.1016/s1386-5056(01)00213-1.

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Ismail, Mahmoud, and James Philbin. "Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format." Journal of Medical Imaging 2, no. 2 (June 24, 2015): 026501. http://dx.doi.org/10.1117/1.jmi.2.2.026501.

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Journal articles on the topic 'DICOM'

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