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A researcher in the field of radiology and computer-aided diagnosis, he has co-authored over 500 journal articles and conference proceedings papers and is a coinventor on 12 patents. [1] His lab has conducted research applying artificial intelligence and deep learning to radiology. [2] [3] [4]
Marti-Bonmati's research interests include liver MR [13] and CT, abdominal [14] and pelvic MRI, contrast agents, [15] image processing, and imaging biomarkers. [8] [16] He also worked in the evaluation of liver segmentation, [17] the quantification of emphysema and pulmonary vascularization, joint cartilage thickness, [18] schizophrenia, and the microstructure, rigidity, and fragility of the ...
These include DICOM (Digital Imaging and Communications in Medicine), Health Level 7 (HL7), International Organization for Standardization (ISO), and Artificial Intelligence protocols. Current research surrounding Imaging Informatics has a focus on Artificial Intelligence (AI) and Machine Learning (ML). These new technologies are being used to ...
Journal of Diagnostic Medical Sonography; Journal of Medical Imaging; Journal of Medical Imaging and Radiation Oncology; Journal of Nuclear Cardiology; Journal of Nuclear Medicine Technology; The Journal of Nuclear Medicine; Journal of Radiation Research; Journal of the American College of Radiology; Journal of Vascular and Interventional Radiology
The field of radiology has undergone the digital transformation almost 15 years ago, not because radiology is more advanced, but there are fundamental differences between digital images in radiology and digital pathology: The image source in radiology is the (alive) patient, and today in most cases, the image is even primarily captured in ...
Projectional imaging of digital radiography can be done by X-ray detectors that directly convert the image to digital format. Alternatively, phosphor plate radiography is where the image is first taken on a photostimulable phosphor (PSP) plate which is subsequently scanned by a mechanism called photostimulated luminescence .
The Digital Mammographic Imaging Screening Trial (DMIST) is a multi-institutional research study, beginning in 2001, on the efficacy for screening of full-field digital mammography (FFDM) compared to conventional film-screen mammography that was sponsored by the U.S. National Cancer Institute and performed by the American College of Radiology Imaging Network (ACRIN).
Journal of Computer Aided Radiology and Surgery; BMC Medical Imaging; In addition the following journals occasionally publish articles describing methods and specific clinical applications of medical image computing or modality specific medical image computing Radiology the official journal of the Radiological Society of North America; NeuroImage
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