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Found 4 papers, 2 papers with code
Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT
DL methods can be designed for AIS lesion detection on CT using the vast quantities of routinely-collected CT brain scan data.
Challenges of building medical image datasets for development of deep learning software in stroke
Despite the large amount of brain CT data generated in clinical practice, the availability of CT datasets for deep learning (DL) research is currently limited.
Spatio-Angular Convolutions for Super-resolution in Diffusion MRI
Diffusion MRI (dMRI) is a widely used imaging modality, but requires long scanning times to acquire high resolution datasets.
Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder
In this work we develop a 3D recurrent convolutional neural network (RCNN) capable of super-resolving dMRI volumes in the angular (q-space) domain.
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