Military traumatic brain injury: a challenge straddling neurology and psychiatry

LZ Kong, RL Zhang, SH Hu, JB Lai - Military medical research, 2022 - Springer
Military psychiatry, a new subcategory of psychiatry, has become an invaluable, intangible
effect of the war. In this review, we begin by examining related military research …

Traumatic brain injury: imaging patterns and complications

AD Schweitzer, SN Niogi, CT Whitlow, AJ Tsiouris - Radiographics, 2019 - pubs.rsna.org
While the diagnosis of traumatic brain injury (TBI) is a clinical decision, neuroimaging
remains vital for guiding management on the basis of identification of intracranial pathologic …

Fast unsupervised brain anomaly detection and segmentation with diffusion models

WHL Pinaya, MS Graham, R Gray, PF Da Costa… - … Conference on Medical …, 2022 - Springer
Deep generative models have emerged as promising tools for detecting arbitrary anomalies
in data, dispensing with the necessity for manual labelling. Recently, autoregressive …

[HTML][HTML] Unsupervised brain imaging 3D anomaly detection and segmentation with transformers

WHL Pinaya, PD Tudosiu, R Gray, G Rees… - Medical Image …, 2022 - Elsevier
Pathological brain appearances may be so heterogeneous as to be intelligible only as
anomalies, defined by their deviation from normality rather than any specific set of …

[HTML][HTML] Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation

K Kamnitsas, C Ledig, VFJ Newcombe… - Medical image …, 2017 - Elsevier
We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural
Network for the challenging task of brain lesion segmentation. The devised architecture is …

Big data analysis for brain tumor detection: Deep convolutional neural networks

J Amin, M Sharif, M Yasmin, SL Fernandes - Future Generation Computer …, 2018 - Elsevier
Brain tumor detection is an active area of research in brain image processing. In this work, a
methodology is proposed to segment and classify the brain tumor using magnetic resonance …

Novel approach to classify brain tumor based on transfer learning and deep learning

S Jain, V Jain - International Journal of Information Technology, 2023 - Springer
Transfer learning strategies were used to develop a unique method in the field of medicine.
Investigation in this study suggests an ensemble technique for early brain tumor detection …

Deep learning applications for acute stroke management

IR Chavva, AL Crawford, MH Mazurek… - Annals of …, 2022 - Wiley Online Library
Brain imaging is essential to the clinical care of patients with stroke, a leading cause of
disability and death worldwide. Whereas advanced neuroimaging techniques offer …

[HTML][HTML] Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction

A Irimia, B Wang, SR Aylward, MW Prastawa… - NeuroImage: Clinical, 2012 - Elsevier
Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view
that multimodal neuroimaging using structural and functional magnetic resonance imaging …

The challenge of mild traumatic brain injury: role of biochemical markers in diagnosis of brain damage

S Mondello, K Schmid, RP Berger… - Medicinal research …, 2014 - Wiley Online Library
During the past decade there has been an increasing recognition of the incidence of mild
traumatic brain injury (mTBI) and a better understanding of the subtle neurological and …