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/2023-MindSpore-1/ms-code-183
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-207
https://github.com/2023-MindSpore-1/ms-code-208
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/IRN
IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/PSPNet
https://github.com/2023-MindSpore-1/ms-code-215/tree/main/Pix2Pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/UNet3%2B
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tinydarknet
https://github.com/2023-MindSpore-1/ms-code-221/tree/main/3D-LWNet
The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/Alexnet
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-46
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/Pix2PixHD
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-6/tree/main/cct
https://github.com/2023-MindSpore-1/ms-code-66
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-67
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/UNet3%2B
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tinydarknet
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/vnet
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
https://github.com/2023-MindSpore-4/Code-5/tree/main/meta-baseline
https://github.com/2023-MindSpore-4/Code10/tree/main/MaskRCNN
https://github.com/2023-MindSpore-4/Code10/tree/main/Unet
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/2023-MindSpore-4/Code10/tree/main/hardnet
https://github.com/2023-MindSpore-4/Code11/tree/main/SPPNet
SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation
https://github.com/2023-MindSpore-4/Code11/tree/main/SinGAN
SinGAN-Seg: Synthetic training data generation for medical image segmentation
https://github.com/2023-MindSpore-4/Code14/tree/main/SPPNet
SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation
https://github.com/2023-MindSpore-4/Code14/tree/main/SinGAN
SinGAN-Seg: Synthetic training data generation for medical image segmentation
https://github.com/2023-MindSpore-4/Code7/tree/main/SPPNet
SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation
https://github.com/2023-MindSpore-4/Code9/tree/main/MaskRCNN
https://github.com/2024-MindSpore-1/Code6/tree/main/3D_DenseNet
https://github.com/2024-MindSpore-1/Code7/tree/main/convmixer
CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network
https://github.com/44aayush/Denoising-and-Enhancement
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/4uiiurz1/pytorch-nested-unet
UNet++: A Nested U-Net Architecture for Medical Image Segmentation
https://github.com/AICIP-UTK/spacenet-round3
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/AKASH2907/bird-species-classification
https://github.com/AKASH2907/bird_species_classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.