Papers with Code 아카이브
Medical Image Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 31
- 평가표
- 49
- 보존된 평가 기록
- 332
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/leonardhan1979/fasterRCNN
https://github.com/libreai/neural-painters-x
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/lichengunc/mask-faster-rcnn
https://github.com/lihaoliu-cambridge/unsupervised-medical-image-segmentation
Contrastive Registration for Unsupervised Medical Image Segmentation
https://github.com/lincaiming/py-faster-rcnn-update
https://github.com/lincaiming/py-faster-rcnn-windows
https://github.com/linxi159/GAN-training-tricks
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/linxi159/Tips-and-tricks-to-train-GANs
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/lionelmessi6410/ntga
https://github.com/liutingwed/sam-not-perfect
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
https://github.com/liuzhuang13/DenseNetCaffe
https://github.com/lixiaolei1982/DenseNet-base-Mask-RCNN-for-Human-Pose-Estimation
https://github.com/ljllili23/unet_baseline
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/longcw/roialign.pytorch
https://github.com/looooongchen/instseg
https://github.com/louisyuzhe/car-damage-detector
https://github.com/lpirola13/flower-recognizer
https://github.com/lpirola13/flower_recognizer
https://github.com/lrr-rachel/PCDUNet
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/ls5122/mask-rcnn
https://github.com/lseventeen/FR-UNet
https://github.com/lseventeen/dias
PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation
https://github.com/ltracegeo/deep-mineralogical-segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/lucas-rbnt/bm-mae
https://github.com/lucasgb2/skinlession
https://github.com/lucidrains/imagen-pytorch
A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation
https://github.com/lucylow/salty-wet-man
https://github.com/lukeandshuo/IR2VI_journal
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/lukoucky/image_recommendation
https://github.com/luoxd1996/wsl4mis
https://github.com/lurenhaothu/CWMI
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/luvgold/auotofoucus3D-Brats
https://github.com/lxFang2022/DALE
Minding Fuzzy Regions: A Data-driven Alternating Learning Paradigm for Stable Lesion Segmentation
https://github.com/lxy5513/Multi-Style-Transfer
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
https://github.com/lyffly/Segmentation_with_my_dataset
U-Net: Convolutional Networks for Biomedical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.