The role of generative adversarial networks in brain MRI: a sco** review
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …
made available. Generative adversarial networks (GANs) showed a lot of potential to …
Synthetic atrophy for longitudinal cortical surface analyses
In the fields of longitudinal cortical segmentation and surface-based cortical thickness (CT)
measurement, difficulty in assessing accuracy remains a substantial limitation due to the …
measurement, difficulty in assessing accuracy remains a substantial limitation due to the …
[HTML][HTML] Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants
P Bautin, J Cohen-Adad - NeuroImage: Clinical, 2021 - Elsevier
Spinal cord atrophy is a well-known biomarker in multiple sclerosis (MS) and other diseases.
It is measured by segmenting the spinal cord on an MRI image and computing the average …
It is measured by segmenting the spinal cord on an MRI image and computing the average …
An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images
Hematoma expansion (HE) occurs in 20% of patients with hemorrhagic stroke within 24 h of
onset, and it is associated with a poorer patient outcome. From a clinical point of view …
onset, and it is associated with a poorer patient outcome. From a clinical point of view …
Probabilistic brain extraction in MR images via conditional generative adversarial networks
Brain extraction, or the task of segmenting the brain in MR images, forms an essential step
for many neuroimaging applications. These include quantifying brain tissue volumes …
for many neuroimaging applications. These include quantifying brain tissue volumes …