https://github.com/zhuye98/icl
공식 코드Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation
Papers with Code 아카이브
Medical Image Segmentation
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- 31
- 평가표
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- 보존된 평가 기록
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Medical Image Segmentation is a computer vision task that involves dividing an medical image into multiple segments, where each segment represents a different object or structure of interest in the image. The goal of medical image segmentation is to provide a precise and accurate representation of the objects of interest within the image, typically for the purpose of diagnosis, treatment planning, and quantitative analysis.
<span style="color:grey; opacity: 0.6">( Image credit: IVD-Net )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zihuanqiu/BDG-Net
공식 코드BDG-Net: Boundary Distribution Guided Network for Accurate Polyp Segmentation
https://github.com/zinic95/HFTrans
공식 코드https://github.com/ziyangwang007/cv-ssl-mis
공식 코드https://github.com/ziyangwang007/mamba-unet
공식 코드Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation
https://github.com/zjlab-ammi/q-net
공식 코드https://github.com/zjufanlab/scdeepsort
공식 코드https://github.com/zjugivelab/scaleformer
공식 코드https://github.com/zombasy/fsg-net-pytorch
공식 코드Full-scale Representation Guided Network for Retinal Vessel Segmentation
https://github.com/zongzi13545329/simada
공식 코드SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes
https://github.com/zoujx96/DR-segmentation
공식 코드Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
https://github.com/zs1314/skinmamba
공식 코드https://github.com/zx-pan/mdm
공식 코드https://github.com/zx33/apaunet
공식 코드APAUNet: Axis Projection Attention UNet for Small Target in 3D Medical Segmentation
https://github.com/zymissy/ccvim
공식 코드Merging Context Clustering with Visual State Space Models for Medical Image Segmentation
https://github.com/zyun-y/dconnnet
공식 코드Directional Connectivity-based Segmentation of Medical Images
https://github.com/zzzqzhou/dual-normalization
공식 코드https://github.com/zzzqzhou/ram-dsir
공식 코드https://github.com/zzzsn/miccai2022-autopet
공식 코드https://gitlab.com/emil-benedykciuk/u-net-darts-tensorflow
공식 코드https://gitlab.com/nct_tso_public/laparoscopic-image-2-image-translation
공식 코드https://zenodo.org/record/15255556
공식 코드GOUHFI: a novel contrast- and resolution-agnostic segmentation tool for Ultra-High Field MRI
https://github.com/01pooja10/Sketch-to-Shoe
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/0492wzl/tensorflow_slim_densenet
https://github.com/04RR/SOTA-Vision
TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
https://github.com/0bserver07/Keras-SegNet-Basic
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/0jason000/DenseNet
https://github.com/0xzayd/Wnet-cGAN
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/1044197988/TF.Keras-Commonly-used-models
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/163GitHub/AI
https://github.com/16xccheng/keras-unet
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/198808xc/OrganSegC2F
A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
https://github.com/198808xc/OrganSegRSTN
A Fixed-Point Model for Pancreas Segmentation in Abdominal CT Scans
https://github.com/2023-MindSpore-1/ms-code-118
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-122
MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-146
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.