https://github.com/taigw/geodesic_distance
DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation
Papers with Code 아카이브
Brain Tumor Segmentation
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Brain Tumor Segmentation is a medical image analysis task that involves the separation of brain tumors from normal brain tissue in magnetic resonance imaging (MRI) scans. The goal of brain tumor segmentation is to produce a binary or multi-class segmentation map that accurately reflects the location and extent of the tumor.
<span style="color:grey; opacity: 0.6">( Image credit: Brain Tumor Segmentation with Deep Neural Networks )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tbymiracle/Brain-Tumor-Segmentation-Paddle
https://github.com/tobiasforest/mimics/tree/main/TBraTS_Zou_MICCAI2022
https://github.com/trichtu/ConvLSTM-RAU-net
https://github.com/trichtu/Recurrent_Attention_U_net
https://github.com/trungnhanuchiha/VAE_BRATS2018
3D MRI brain tumor segmentation using autoencoder regularization
https://github.com/vankhoa21991/medicalImgSEg
https://github.com/wenhui0206/Robust-TransBTS
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
https://github.com/wjcheon/MedicalImageSegmentation_Pytorch
https://github.com/yangyucheng000/-acn_mindspore
ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities
https://github.com/yangyucheng000/Paper-3/tree/main/msBraVL-master
https://github.com/yingkaisha/keras-unet-collection
https://github.com/yykzjh/pmfsnet
https://github.com/zhyjsiat/a-two-stage-cyclegan-ve-brats2020
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.