https://github.com/AMiiR-S/Inceptnet_cancer_recognition
공식 코드INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses
Papers with Code 아카이브
Skin Lesion 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/AnandK27/GS-TransUNet
공식 코드https://github.com/DIDSR/ssynth-release
공식 코드S-SYNTH: Knowledge-Based, Synthetic Generation of Skin Images
https://github.com/Guo-Xiaoqing/Skin-Seg
공식 코드Complementary Network with Adaptive Receptive Fields for Melanoma Segmentation
https://github.com/HiLab-git/CA-Net
공식 코드https://github.com/MinaJf/DRU-net
공식 코드DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image Segmentation
https://github.com/NoviceMAn-prog/MSRF-Net
공식 코드MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
https://github.com/SiyuanYan1/PanDerm
공식 코드A Multimodal Vision Foundation Model for Clinical Dermatology
https://github.com/WuJunde/MrPrism
공식 코드Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle
https://github.com/aryan-at-ul/electronic-imaging-2025-paper-4492
공식 코드https://github.com/asgsaeid/KernelizedManifoldMapping
공식 코드A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
https://github.com/baobao0926/asp-vmunet
공식 코드ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation
https://github.com/chunyuyuan/mucm-net
공식 코드MUCM-Net: A Mamba Powered UCM-Net for Skin Lesion Segmentation
https://github.com/chunyuyuan/ucm-net
공식 코드UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNN
https://github.com/dipaco/mole-classification
공식 코드Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging
https://github.com/fangzhuoyi/xlstm-vmunet
공식 코드https://github.com/feevos/ssg2
공식 코드https://github.com/fitushar/Skin-lesion-Segmentation-using-grabcut
공식 코드Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space
https://github.com/haoshao-nku/medical_seg
공식 코드MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention
https://github.com/hectorcarrion/fedd
공식 코드https://github.com/hritam-98/MFSNet
공식 코드MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation
https://github.com/jacobzhaoziyuan/SAAL
공식 코드Self-supervised Assisted Active Learning for Skin Lesion Segmentation
https://github.com/jcruan519/ege-unet
공식 코드EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation
https://github.com/jcruan519/malunet
공식 코드MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation
https://github.com/jcwang123/BA-Transformer
공식 코드https://github.com/jcwang123/xboundformer
공식 코드XBound-Former: Toward Cross-scale Boundary Modeling in Transformers
https://github.com/jingyechen/mt-transunet
공식 코드https://github.com/jwicaksana/fedmix
공식 코드FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation
https://github.com/kakumarabhishek/Illumination-based-Transformations-Skin-Lesion-Segmentation
공식 코드Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images
https://github.com/kakumarabhishek/MCC-Loss
공식 코드https://github.com/kamruleee51/Skin-Lesion-Segmentation-Using-Proposed-DSNet
공식 코드https://github.com/learningtitans/isbi2017-part1
공식 코드https://github.com/learningtitans/isbi2017-part3
공식 코드https://github.com/luo-lorry/Stylized-Medical-Segmentation
공식 코드Structure-Aware Stylized Image Synthesis for Robust Medical Image Segmentation
https://github.com/masih4/Skin-lesion-segmentation-effects-of-the-classification-perfromnce
공식 코드The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification
https://github.com/mindflow-institue/daeformer
공식 코드DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.