Papers with Code 아카이브

MRI segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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코드

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

https://github.com/BBillot/lab2im

A Learning Strategy for Contrast-agnostic MRI Segmentation

https://github.com/adalca/neurite

Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

https://github.com/denizlab/2019_IWOAI_Challenge

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

https://github.com/gaetanosettembre/BrainTumor_clf_TDA

https://github.com/mazurowski-lab/SlicerSegmentHumanBody

SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI

https://github.com/nafiuny/Optimized_TumorClassifierResNetSD

Deep Multimodal Guidance for Medical Image Classification

https://github.com/vitalab/castor

Cardiac MRI Segmentation with Strong Anatomical Guarantees

https://github.com/voxelmorph/voxelmorph

Unsupervised Deep Learning for Bayesian Brain MRI Segmentation

https://github.com/wehrlimi/generate-pseudo-healthy-knee-mri

SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI

https://github.com/zhiyuns/REHRSeg

REHRSeg: Unleashing the Power of Self-Supervised Super-Resolution for Resource-Efficient 3D MRI Segmentation

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