https://github.com/hms-dbmi/chief
A deep learning framework for efficient pathology image analysis
Papers with Code 아카이브
whole slide images
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/iceli1007/ICIAR2018_BACH_Challenge-DA-Refinenet
DA-RefineNet:A Dual Input Whole Slide Image Segmentation Algorithm Based on Attention
https://github.com/innse/mstar
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model
https://github.com/isyangshu/surgformer
MambaMIL: Enhancing Long Sequence Modeling with Sequence Reordering in Computational Pathology
https://github.com/kaiseem/pointnu-net
https://github.com/konst-int-i/mm-lego
HEALNet: Multimodal Fusion for Heterogeneous Biomedical Data
https://github.com/lely475/softctm
SoftCTM: Cell detection by soft instance segmentation and consideration of cell-tissue interaction
https://github.com/lhaof/cgt
https://github.com/liupei101/psemix
https://github.com/magic-ai4med/keep
A Knowledge-enhanced Pathology Vision-language Foundation Model for Cancer Diagnosis
https://github.com/mahmoodlab/HistoFL
Federated Learning for Computational Pathology on Gigapixel Whole Slide Images
https://github.com/mahmoodlab/SISH
https://github.com/mahmoodlab/titan
PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology
https://github.com/ohshyuk5/Memory-based-Exchangeable-Model
Learning Permutation Invariant Representations using Memory Networks
https://github.com/okunator/Dippa
https://github.com/reeered/FALFormer-MindSpore
FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification
https://github.com/uit-hdl/hovernet-pipeline
https://github.com/vqdang/hover_net
https://github.com/wisdomikezogwo/quilt1m
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.