Colorectal Gland Segmentation:
7 papers with code • 2 benchmarks • 3 datasets
Kvasir-SEG
STARE
Kvasir
Most implemented papers
U-Net: Convolutional Networks for Biomedical Image Segmentation
labmlai/annotated_deep_learning_paper_implementations
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There is large consent that successful training of deep networks requires many thousand annotated training samples.
Rotation equivariant vector field networks
di-marcos/RotEqNet
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ICCV 2017
In many computer vision tasks, we expect a particular behavior of the output with respect to rotations of the input image.
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
Histology images are inherently symmetric under rotation, where each orientation is equally as likely to appear.
Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical Image Segmentation
HiLab-git/SSL4MIS
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CVPR 2023
Although recent works in semi-supervised learning (SemiSL) have accomplished significant success in natural image segmentation, the task of learning discriminative representations from limited annotations has been an open problem in medical images.
Group Equivariant Convolutional Networks
adambielski/pytorch-gconv-experiments
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We introduce Group equivariant Convolutional Neural Networks (G-CNNs), a natural generalization of convolutional neural networks that reduces sample complexity by exploiting symmetries.
Machine learning approach for segmenting glands in colon histology images using local intensity and texture features
A multilevel random forest technique in a hierarchical way is proposed.
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis
tueimage/se2cnn
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This study is focused on histopathology image analysis applications for which it is desirable that the arbitrary global orientation information of the imaged tissues is not captured by the machine learning models.
