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Lesion Segmentation

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하위 태스크: 0
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/schroeterjulien/midl-2022-segmentation-consistent-lesion-counting

공식 코드

Segmentation-Consistent Probabilistic Lesion Counting

https://github.com/scott-yjyang/vivim

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Vivim: a Video Vision Mamba for Medical Video Segmentation

https://github.com/selgroup/sled

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Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs

https://github.com/sepidehamiri/pet_seg_unet

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Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time Augmentation

https://github.com/sfu-mial/skin-lesion-segmentation-survey

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A Survey on Deep Learning for Skin Lesion Segmentation

https://github.com/sfu-mial/styleseg

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Segmentation Style Discovery: Application to Skin Lesion Images

https://github.com/shinkaiz/clcc-semi

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Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation

https://github.com/shubhaminnani/egan

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Generative Adversarial Networks based Skin Lesion Segmentation

https://github.com/siyi-wind/avit

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AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets

https://github.com/siyi-wind/mdvit

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MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets

https://github.com/sqbqamar/scalefusionnet

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ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion Segmentation

https://github.com/tabrisrei/isles22_ensemble

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A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge

https://github.com/tanyanair/segmentation_uncertainty

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Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation

https://github.com/tensorflow/models

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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

https://github.com/tinymilky/NeRD

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NeRD: Neural Representation of Distribution for Medical Image Segmentation

https://github.com/tinymilky/RSANet

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RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation

https://github.com/tinymilky/deda

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DAGrid: Directed Accumulator Grid

https://github.com/utkuozbulak/adaptive-segmentation-mask-attack

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Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation

https://github.com/verena-hallitschke/pet-ct-annotate

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Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images based on Physiological and Anatomical Cues

https://github.com/vietthanh2710/ac-mambaseg

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AC-MAMBASEG: An adaptive convolution and Mamba-based architecture for enhanced skin lesion segmentation

https://github.com/vribeiro1/skin-lesion-segmentation-agreement

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Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation

https://github.com/vvjia/sam-swin

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SAM-Swin: SAM-Driven Dual-Swin Transformers with Adaptive Lesion Enhancement for Laryngo-Pharyngeal Tumor Detection

https://github.com/weathon/vcos

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ZS-VCOS: Zero-Shot Outperforms Supervised Video Camouflaged Object Segmentation

https://github.com/wenhui0206/MeanTeacher-DeepMedic

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Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model

https://github.com/wurenkai/MHA-UNet

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Only Positive Cases: 5-fold High-order Attention Interaction Model for Skin Segmentation Derived Classification

https://github.com/wurenkai/UltraLight-VM-UNet

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UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation

https://github.com/wurenkai/h-vmunet

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H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation

https://github.com/wyyu0831/san

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SAN-Net: Learning Generalization to Unseen Sites for Stroke Lesion Segmentation with Self-Adaptive Normalization

https://github.com/xia-xx-cv/lanet-dr

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Lesion-aware network for diabetic retinopathy diagnosis

https://github.com/xinkunwang111/promise

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ProMISe: Promptable Medical Image Segmentation using SAM

https://github.com/xmengli999/Deeply-Supervised-Rotation-Equivariant-Network-for-Lesion-Segmentation

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Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images

https://github.com/xmindflow/Laplacian-Former

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Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection

https://github.com/xmindflow/braincl

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Modality-Independent Brain Lesion Segmentation with Privacy-aware Continual Learning

https://github.com/xq141839/DCSAU-Net

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DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation

https://github.com/yanglanou/patcher

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Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation

https://github.com/yaoppeng/u-net_v2

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U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation

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