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3D Medical Imaging Segmentation

3D medical imaging segmentation is the task of segmenting medical objects of interest from 3D medical imaging.

( Image credit: Elastic Boundary Projection for 3D Medical Image Segmentation )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 31–40 of 41 papers

TitleStatusHype
Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging SegmentationCode0
Pulmonary Artery–Vein Classification in CT Images Using Deep Learning—0
An application of cascaded 3D fully convolutional networks for medical image segmentationCode0
TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary ConvolutionsCode0
3D Densely Convolutional Networks for VolumetricSegmentation—0
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext TaskCode0
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation—0
3D fully convolutional networks for subcortical segmentation in MRI: A large-scale studyCode0
Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image SegmentationCode0
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion SegmentationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Holistic-nested CNNDice Score81.3—Unverified
2Multi-class 3D FCNDice Score76.8—Unverified