Výsledky vyhledávání - "Shekhar S Chandra"

Akademický článek

PREdiction and Diagnosis using Imaging and Clinical biomarkers Trial in Traumatic Brain Injury (PREDICT-TBI) study protocol: an observational, prospective, multicentre cohort study for the prediction of outcome in moderate-to-severe TBI

Autor: Siva Senthuran, Lewis Campbell, Jennifer Fleming, Virginia Newcombe, Michael Reade, Silvia Manzanero, James Walsham, Nathan Brown, Xuan Vinh To, Clifford Pollard, Fatima Nasrallah, Judith Bellapart, Esther Jacobson, Jason Meyer, Janine Stuart, Tracey Evans, Shekhar S Chandra, Jason Ross, James McCullough

Publikováno v: BMJ Open, Vol 13, Iss 4 (2023)

Introduction Traumatic brain injury (TBI) is a heterogeneous condition with a broad spectrum of injury severity, pathophysiological processes and variable outcomes. For moderate-to-severe TBI survivors, recovery is often protracted and outcomes can r

Externí odkaz: https://doaj.org/article/3f950540292844b3b14826ab1bcc2068

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Automated volumetric and statistical shape assessment of cam-type morphology of the femoral head-neck region from clinical 3D magnetic resonance images

Autor: Jessica M. Bugeja, Ying Xia, Shekhar S. Chandra, Nicholas J. Murphy, Jillian Eyles, Libby Spiers, Stuart Crozier, David J. Hunter, Jurgen Fripp, Craig Engstrom

Publikováno v: Quantitative Imaging in Medicine and Surgery. 12:4924-4941

Femoroacetabular impingement (FAI) cam morphology is routinely assessed using manual measurements of two-dimensional (2D) alpha angles which are prone to high rater variability and do not provide direct three-dimensional (3D) data on these osseous fo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8ec3fc8830fbd44c83b752346f33859
https://doi.org/10.21037/qims-22-332

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Deep Neural Networks Predict the Need for CT in Pediatric Mild Traumatic Brain Injury: A Corroboration of the PECARN Rule

Autor: Hanem Ellethy, Shekhar S. Chandra, Fatima A. Nasrallah

Publikováno v: Journal of the American College of Radiology. 19:769-778

Only 10% of CT scans unveil positive findings in mild traumatic brain injury, raising concerns of its overuse in this population. A number of clinical rules have been developed to address this issue, but they still suffer limitations in their specifi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::031924404b5c2934f2d4c46129316820
https://doi.org/10.1016/j.jacr.2022.02.024

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Transformer Compressed Sensing Via Global Image Tokens

Autor: Marlon Bran Lorenzana, Craig Engstrom, Shekhar S. Chandra

Publikováno v: 2022 IEEE International Conference on Image Processing (ICIP).

Convolutional neural networks (CNN) have demonstrated outstanding Compressed Sensing (CS) performance compared to traditional, hand-crafted methods. However, they are broadly limited in terms of generalisability, inductive bias and difficulty to mode

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::015f473bbc479e51d63529ff11938274
https://doi.org/10.1109/icip46576.2022.9897630

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Deep learning in magnetic resonance image reconstruction

Autor: Shekhar S. Chandra, Xinwen Liu, Siyu Liu, Marlon Bran Lorenzana, Stuart Crozier, Steffen Bollmann

Publikováno v: Journal of Medical Imaging and Radiation Oncology. 65:564-577

Magnetic resonance (MR) imaging visualises soft tissue contrast in exquisite detail without harmful ionising radiation. In this work, we provide a state-of-the-art review on the use of deep learning in MR image reconstruction from different image acq

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db54bb356f85edf222c4a24f4ad9bae9
https://doi.org/10.1111/1754-9485.13276

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