Papers with Code 아카이브

Lesion Segmentation

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평가표: 9
보존된 평가 기록: 42

Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.

<span style="color:grey; opacity: 0.6">( Image credit: D-UNet )</span>

코드

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

https://github.com/YanglanOu/LambdaUNet

공식 코드

LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images

https://github.com/YtongXie/MB-DCNN

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A Mutual Bootstrapping Model for Automated Skin Lesion Segmentation and Classification

https://github.com/agaldran/lesion_losses_ood

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On the Optimal Combination of Cross-Entropy and Soft Dice Losses for Lesion Segmentation with Out-of-Distribution Robustness

https://github.com/agnalt/window-shifting

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View it like a radiologist: Shifted windows for deep learning augmentation of CT images

https://github.com/agosl/Orthogonal_Ensemble_Networks

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Orthogonal Ensemble Networks for Biomedical Image Segmentation

https://github.com/ahatamiz/dals

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Deep Active Lesion Segmentation

https://github.com/ahxmeds/autopet2024

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AutoPET Challenge III: Testing the Robustness of Generalized Dice Focal Loss trained 3D Residual UNet for FDG and PSMA Lesion Segmentation from Whole-Body PET/CT Images

https://github.com/ahxmeds/autosegnet

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Generalized Dice Focal Loss trained 3D Residual UNet for Automated Lesion Segmentation in Whole-Body FDG PET/CT Images

https://github.com/ahxmeds/autosegnet2024

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AutoPET Challenge III: Testing the Robustness of Generalized Dice Focal Loss trained 3D Residual UNet for FDG and PSMA Lesion Segmentation from Whole-Body PET/CT Images

https://github.com/ajoshiusc/qrvae

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Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection

https://github.com/alessandro-f/dif-fuse

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Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images

https://github.com/alexanderjaus/autopet3_datadiet

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Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?

https://github.com/alexklwong/subpixel-embedding-segmentation

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Small Lesion Segmentation in Brain MRIs with Subpixel Embedding

https://github.com/alibaba-damo-academy/pixel-lesion-patient-network

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Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network

https://github.com/anissa218/autopet_nnunet

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Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation

https://github.com/arcadelab/DeepDRR

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SyntheX: Scaling Up Learning-based X-ray Image Analysis Through In Silico Experiments

https://github.com/aryan-at-ul/electronic-imaging-2025-paper-4492

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Image Segmentation: Inducing graph-based learning

https://github.com/asgsaeid/KernelizedManifoldMapping

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A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations

https://github.com/avakanski/Attention-Enriched-DL-Model-for-Breast-Tumor-Segmentation

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Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images

https://github.com/baobao0926/asp-vmunet

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ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion Segmentation

https://github.com/biomedical-data-analysis-laboratory/adnet-for-ais-segmentation

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Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation

https://github.com/brainimageanalysis/ici-loss

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Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function

https://github.com/bscs12/bussam

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Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images

https://github.com/c-hepburn/Bone_MRI

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Volume of hyperintense inflammation (VHI): a deep learning-enabled quantitative imaging biomarker of inflammation load in spondyloarthritis

https://github.com/cgpxy/aau-net

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AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images

https://github.com/cgpxy/esknet

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ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation

https://github.com/cgpzy/aau-net

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AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images

https://github.com/chunyuyuan/mucm-net

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MUCM-Net: A Mamba Powered UCM-Net for Skin Lesion Segmentation

https://github.com/chunyuyuan/ucm-net

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UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNN

https://github.com/crazorback/aadg

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AADG: Automatic Augmentation for Domain Generalization on Retinal Image Segmentation

https://github.com/cvblab/anomaly_localization_vae_gcams

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Looking at the whole picture: constrained unsupervised anomaly segmentation

https://github.com/cviu-csu/hrdecoder

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HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation

https://github.com/cviu-csu/m2mrf-lesion-segmentation

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M2MRF: Many-to-Many Reassembly of Features for Tiny Lesion Segmentation in Fundus Images

https://github.com/cwwang1979/CW-nnU-Net-for-PET-CT

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Dual channel CW nnU-Net for 3D PET-CT Lesion Segmentation in 2024 autoPET III Challenge

https://github.com/dipaco/mole-classification

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Automatic skin lesion segmentation on dermoscopic images by the means of superpixel merging

https://github.com/dumyCq/CFPNet

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ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video

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