IEEE Transactions on
Medical Imaging

Impact Factor: 6.685


We publish manuscripts on imaging of body structure, morphology and function, including cell and molecular imaging and all forms of microscopy.

Call for Papers: Second Special Issue on Machine Learning for Image Reconstruction (Closed to new submissions)

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Highlighted Associate Editors

Delia Cabrera DeBuc
Associate Editor
Associate Editor

Dr. Cabrera DeBuc has been an Associate Editor since 2011 and primarily oversees manuscript submissions in the areas of AI, imaging processing, and analysis of medical images.

She received her Ph.D. degree in Applied Physics (2002) from the University of Michigan. Dr. Cabrera DeBuc is currently a Research Associate Professor of Ophthalmology at the Bascom Palmer Eye Institute, University of Miami Miller School of Medicine.

She is a biophysicist with specific training in ocular imaging technology and image analysis. Her research group has been supported by grants from the Juvenile Diabetes Research Foundation, the National Institute of Health, the Alzheimer's Association, the National Institute on Aging, the Finker Frenkel Legacy Foundation, and the National Eye Institute. Her research interests include medical applications of ultrafast laser technology and optical imaging, focusing on the human eye, including the development and use of quantitative... Read more

Dr. Cabrera DeBuc has been an Associate Editor since 2011 and primarily oversees manuscript submissions in the areas of AI, imaging processing, and analysis of medical images.

She received her Ph.D. degree in Applied Physics (2002) from the University of Michigan. Dr. Cabrera DeBuc is currently a Research Associate Professor of Ophthalmology at the Bascom Palmer Eye Institute, University of Miami Miller School of Medicine.

She is a biophysicist with specific training in ocular imaging technology and image analysis. Her research group has been supported by grants from the Juvenile Diabetes Research Foundation, the National Institute of Health, the Alzheimer's Association, the National Institute on Aging, the Finker Frenkel Legacy Foundation, and the National Eye Institute. Her research interests include medical applications of ultrafast laser technology and optical imaging, focusing on the human eye, including the development and use of quantitative ophthalmic imaging analyses to enhance ocular health capabilities. Specifically, she has focused her research on the early detection of diabetic retinopathy using advanced optical imaging.

Besides ophthalmic-image processing research, she is also actively involved in taking the leading role in ocular telehealth applications and clinical research related to novel ocular imaging biomarkers for the central nervous system's neurodegenerative diseases, such as multiple sclerosis, Parkinson's, and Alzheimer's disease. Dr. Cabrera DeBuc has presented nationally and internationally on various aspects of medical image processing and novel imaging biomarker development, emphasizing ophthalmology, data science, neuroscience, and vision science. She is also an editorial board member of Scientific Reports (Nature) and a Fellow member of the SPIE.

Dr. Cabrera DeBuc has been a proud member of the medical imaging community as an AE for TMI throughout her career. She has refined quantitative tools and introduced innovative measures to analyze retinal images using fundamental principles from physics to quantify retinal structure-function abnormalities and treatment-induced changes in patients with ocular and neurodegenerative diseases. She is also devoted to Artificial Intelligence applications for disease diagnosis, running a multidisciplinary lab, and collaborating extensively with national and international investigators. Besides, she is an external advisory board member of the EU-funded Marie Skłodowska-Curie Innovative Training Network, "CLARIFY – CLoud ARtificial Intelligence For pathologY. "She is also the CEO and Founder of iScreen 2 Prevent, LLC, a University of Miami's spinoff company aiming to commercialize an AI-based screening platform to predict persons at risk of AD in primary and community health care settings.

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Holger Roth
Associate Editor
Associate Editor

Dr. Roth has been an Associate Editor since 2018 and primarily oversees manuscript submissions in the areas of medical image analysis, like medical image segmentation, computer-aided detection, and diagnosis.

Dr. Roth is a Sr. Applied Research Scientist at NVIDIA focusing on deep learning for medical imaging. He has been working closely with clinicians and academics over the past several years to develop deep learning-based medical image computing and computer-aided detection models for radiological applications, including federated learning for building more robust and clinically useful AI models.

Dr. Roth holds a Ph.D. from University College London, UK, and has been an Assistant Research Professor at Nagoya University, Japan, after completing a Visiting Research Fellow position at the National Institutes of Health, USA.

Dr. Roth has been serving as an Area Chair for MICCAI and MIDL in past years. In 2018, he was awarded... Read more

Dr. Roth has been an Associate Editor since 2018 and primarily oversees manuscript submissions in the areas of medical image analysis, like medical image segmentation, computer-aided detection, and diagnosis.

Dr. Roth is a Sr. Applied Research Scientist at NVIDIA focusing on deep learning for medical imaging. He has been working closely with clinicians and academics over the past several years to develop deep learning-based medical image computing and computer-aided detection models for radiological applications, including federated learning for building more robust and clinically useful AI models.

Dr. Roth holds a Ph.D. from University College London, UK, and has been an Assistant Research Professor at Nagoya University, Japan, after completing a Visiting Research Fellow position at the National Institutes of Health, USA.

Dr. Roth has been serving as an Area Chair for MICCAI and MIDL in past years. In 2018, he was awarded the MICCAI Young Scientist Publication Impact Award.

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