Papers with Code 아카이브

Semi-supervised Medical Image Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 7
보존된 평가 기록: 18

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/HiLab-git/DTC

공식 코드

Semi-supervised Medical Image Segmentation through Dual-task Consistency

https://github.com/HiLab-git/SSL4MIS

공식 코드

Mutual Consistency Learning for Semi-supervised Medical Image Segmentation

https://github.com/JuzhengMiao/CPC-SAM

공식 코드

Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation

https://github.com/LiheYoung/UniMatch

공식 코드

Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation

https://github.com/QingtaoPan/DuSSS

공식 코드

DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image Segmentation

https://github.com/YichiZhang98/DTML

공식 코드

Dual-Task Mutual Learning for Semi-Supervised Medical Image Segmentation

https://github.com/aieson/crossmatch

공식 코드

CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation

https://github.com/aigeeksgroup/sss

공식 코드

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation

https://github.com/aijinrjinr/mlb-seg

공식 코드

Consistency-guided Meta-Learning for Bootstrapping Semi-Supervised Medical Image Segmentation

https://github.com/apple1986/samatch

공식 코드

A SAM-guided and Match-based Semi-Supervised Segmentation Framework for Medical Imaging

https://github.com/axi404/pmt

공식 코드

PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image Segmentation

https://github.com/binycn/dcpa

공식 코드

Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation for Semi-Supervised Medical Image Segmentation

https://github.com/briley-byl123/mper

공식 코드

Multi-Prototype Embedding Refinement for Semi-Supervised Medical Image Segmentation

https://github.com/caoluyang0830/cvbm

공식 코드

Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation

https://github.com/charlesyou999648/MONA

공식 코드

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation with Extremely Limited Labels

https://github.com/charlesyou999648/action

공식 코드

ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast

https://github.com/charlesyou999648/arco

공식 코드

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

https://github.com/chy-upc/abd

공식 코드

Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation

https://github.com/cuhk-aim-group/diffrect

공식 코드

DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation

https://github.com/deepmed-lab-ecnu/bcp

공식 코드

Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation

https://github.com/deepmed-lab-ecnu/magicnet

공식 코드

MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery

https://github.com/fazhan-cs/dcp

공식 코드

Dual-Teacher Ensemble Models with Double-Copy-Paste for 3D Semi-Supervised Medical Image Segmentation

https://github.com/guanghaozhu663/astmatch

공식 코드

AstMatch: Adversarial Self-training Consistency Framework for Semi-Supervised Medical Image Segmentation

https://github.com/gugull123/stac

공식 코드

Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image Segmentation

https://github.com/hengcai-nju/desco

공식 코드

Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation

https://github.com/herschel555/caml

공식 코드

Correlation-Aware Mutual Learning for Semi-supervised Medical Image Segmentation

https://github.com/himashi92/Duo-SegNet

공식 코드

Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image Segmentation

https://github.com/hritam-98/ict-medseg

공식 코드

An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation

https://github.com/hsiangyuzhao/rcps

공식 코드

RCPS: Rectified Contrastive Pseudo Supervision for Semi-Supervised Medical Image Segmentation

https://github.com/huiimin5/aua

공식 코드

Exploring Feature Representation Learning for Semi-supervised Medical Image Segmentation

https://github.com/jiahechen2002/dcf

공식 코드

Decoupled Competitive Framework for Semi-supervised Medical Image Segmentation

https://github.com/jianf-wang/gbdl

공식 코드

Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation

https://github.com/jizongFox/Self-paced-Contrastive-Learning

공식 코드

Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels

https://github.com/justlfc03/dfcps

공식 코드

Semi-supervised Medical Image Segmentation Method Based on Cross-pseudo Labeling Leveraging Strong and Weak Data Augmentation Strategies

https://github.com/kathyliu579/contrastivecross-teachingwithregistration

공식 코드

Learning Semi-Supervised Medical Image Segmentation from Spatial Registration

https://github.com/koncle/coranet

공식 코드

Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.