Search Results for author:
Found 7 papers, 4 papers with code
Sauron U-Net: Simple automated redundancy elimination in medical image segmentation via filter pruning
We present Sauron, a filter pruning method that eliminates redundant feature maps by discarding the corresponding filters with automatically-adjusted layer-specific thresholds.
Automatic cerebral hemisphere segmentation in rat MRI with lesions via attention-based convolutional neural networks
We present MedicDeepLabv3+, a convolutional neural network that is the first completely automatic method to segment cerebral hemispheres in magnetic resonance (MR) volumes of rats with lesions.
Region-wise Loss for Biomedical Image Segmentation
We show that, under the proposed RW loss framework, certain loss functions, such as Active Contour and Boundary loss, can be reformulated similarly with appropriate RW maps, thus revealing their underlying similarities and a new perspective to understand these loss functions.
Transfer Learning in Magnetic Resonance Brain Imaging: a Systematic Review
We found 129 articles that applied transfer learning to brain MRI tasks.
RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation
RatLesNetv2 obtained similar to higher Dice coefficient values than the other ConvNets and it produced much more realistic and compact segmentations with notably fewer holes and lower Hausdorff distance.
Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry
These last two measurements were derived from the T1-weighted MR images using cortical surfaces produced by the CIVET pipeline.
Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks
Several automatic methods have been developed for different human brain MRI segmentation, but little research has targeted automatic rodent lesion segmentation.
