Colorectal Gland Segmentation:
7 papers with code • 2 benchmarks • 3 datasets
Kvasir-SEG
STARE
Kvasir
Latest papers
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.
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.
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.
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.
Rotation equivariant vector field networks
In many computer vision tasks, we expect a particular behavior of the output with respect to rotations of the input image.
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.
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.
