ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
MR Hernandez Petzsche, E de la Rosa, U Hanning… - Scientific data, 2022 - nature.com
Magnetic resonance imaging (MRI) is an important imaging modality in stroke. Computer
based automated medical image processing is increasingly finding its way into clinical …
based automated medical image processing is increasingly finding its way into clinical …
M3T: three-dimensional Medical image classifier using Multi-plane and Multi-slice Transformer
In this study, we propose a three-dimensional Medical image classifier using Multi-plane
and Multi-slice Transformer (M3T) network to classify Alzheimer's disease (AD) in 3D MRI …
and Multi-slice Transformer (M3T) network to classify Alzheimer's disease (AD) in 3D MRI …
Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury
Axonal injury is a key determinant of long-term outcomes after traumatic brain injury (TBI) but
has been difficult to measure clinically. Fluid biomarker assays can now sensitively quantify …
has been difficult to measure clinically. Fluid biomarker assays can now sensitively quantify …
Analyzing magnetic resonance imaging data from glioma patients using deep learning
The quantitative analysis of images acquired in the diagnosis and treatment of patients with
brain tumors has seen a significant rise in the clinical use of computational tools. The …
brain tumors has seen a significant rise in the clinical use of computational tools. The …
Deep learning of brain magnetic resonance images: A brief review
Magnetic resonance imaging (MRI) is one of the most popular techniques in brain science
and is important for understanding brain function and neuropsychiatric disorders. However …
and is important for understanding brain function and neuropsychiatric disorders. However …
Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study
CJ Preetha, H Meredig, G Brugnara… - The Lancet Digital …, 2021 - thelancet.com
Background Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue
contrast during MRI scans and play a crucial role in the management of patients with cancer …
contrast during MRI scans and play a crucial role in the management of patients with cancer …
The brain tumor segmentation (brats-mets) challenge 2023: Brain metastasis segmentation on pre-treatment mri
The translation of AI-generated brain metastases (BM) segmentation into clinical practice
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS …
[HTML][HTML] Accurate brain‐age models for routine clinical MRI examinations
DA Wood, S Kafiabadi, A Al Busaidi, E Guilhem… - Neuroimage, 2022 - Elsevier
Convolutional neural networks (CNN) can accurately predict chronological age in healthy
individuals from structural MRI brain scans. Potentially, these models could be applied …
individuals from structural MRI brain scans. Potentially, these models could be applied …
Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study
Objectives Gadolinium-based contrast agents (GBCAs) have become an integral part in
daily clinical decision making in the last 3 decades. However, there is a broad consensus …
daily clinical decision making in the last 3 decades. However, there is a broad consensus …
Brain aging among racially and ethnically diverse middle-aged and older adults
Importance Neuroimaging studies have documented racial and ethnic disparities in brain
health in old age. It remains unclear whether these disparities are apparent in midlife …
health in old age. It remains unclear whether these disparities are apparent in midlife …