Ischemic Stroke Lesion Segmentation
7 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation
We evaluate the results both qualitatively by visual comparison of generated MR to ground truth, as well as quantitatively by training fully convolutional neural networks that make use of generated MR data inputs to perform ischemic stroke lesion segmentation.
Ischemic Stroke Lesion Segmentation in CT Perfusion Scans using Pyramid Pooling and Focal Loss
We present a fully convolutional neural network for segmenting ischemic stroke lesions in CT perfusion images for the ISLES 2018 challenge.
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities
First, instead of combining the available image modalities at the input, each of them is processed in a different path to better exploit their unique information.
Uncertainty quantification using Bayesian neural networks in classification: Application to ischemic stroke lesion segmentation
Most recent research of neural networks in the field of computer vision has focused on improving accuracy of point predictions by developing various network architectures or learning algorithms.
