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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/elchiou/DA

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Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation

https://github.com/endo-angel/ct-angel

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Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients

https://github.com/etjoa003/medical_imaging

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Enhancing the Extraction of Interpretable Information for Ischemic Stroke Imaging from Deep Neural Networks

https://github.com/ezequieldlrosa/isles22

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ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset

https://github.com/fangzhuoyi/xlstm-vmunet

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When Mamba Meets xLSTM: An Efficient and Precise Method with the xLSTM-VMUNet Model for Skin lesion Segmentation

https://github.com/faresbougourzi/d-trattunet

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D-TrAttUnet: Toward Hybrid CNN-Transformer Architecture for Generic and Subtle Segmentation in Medical Images

https://github.com/federicospagnolo/IES

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Instance-level quantitative saliency in multiple sclerosis lesion segmentation

https://github.com/feevos/ssg2

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SSG2: A new modelling paradigm for semantic segmentation

https://github.com/fitushar/Skin-lesion-Segmentation-using-grabcut

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Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space

https://github.com/freesurfer/freesurfer/tree/dev/samseg

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An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation

https://github.com/hakal104/autopetiii

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Autopet III challenge: Incorporating anatomical knowledge into nnUNet for lesion segmentation in PET/CT

https://github.com/han-liu/moddropplusplus

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ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities

https://github.com/haoshao-nku/medical_seg

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MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis Attention

https://github.com/haoxuanli-thu/hcma-unet

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HCMA-UNet: A Hybrid CNN-Mamba UNet with Axial Self-Attention for Efficient Breast Cancer Segmentation

https://github.com/hectorcarrion/fedd

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FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification

https://github.com/hilab-git/pf-net

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Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention

https://github.com/hritam-98/MFSNet

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MFSNet: A Multi Focus Segmentation Network for Skin Lesion Segmentation

https://github.com/hrlblab/glo-in-one_v2

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Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology

https://github.com/hsiangyuzhao/PANet

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Prior Attention Network for Multi-Lesion Segmentation in Medical Images

https://github.com/hszhao/PSPNet

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Pyramid Scene Parsing Network

https://github.com/huanglizi/stpnet

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STPNet: Scale-aware Text Prompt Network for Medical Image Segmentation

https://github.com/ictlab-unict/attention-cnn-MS-segmentation

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Boosting multiple sclerosis lesion segmentation through attention mechanism

https://github.com/igondia/matconvnet-dermoscopy

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Incorporating the Knowledge of Dermatologists to Convolutional Neural Networks for the Diagnosis of Skin Lesions

https://github.com/imatge-upc/liverseg-2017-nipsws

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Detection-aided liver lesion segmentation using deep learning

https://github.com/ivadomed/ms-challenge-2021

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Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge

https://github.com/jacobzhaoziyuan/SAAL

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Self-supervised Assisted Active Learning for Skin Lesion Segmentation

https://github.com/jcruan519/ege-unet

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EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation

https://github.com/jcruan519/malunet

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MALUNet: A Multi-Attention and Light-weight UNet for Skin Lesion Segmentation

https://github.com/jcwang123/BA-Transformer

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Boundary-aware Transformers for Skin Lesion Segmentation

https://github.com/jcwang123/xboundformer

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XBound-Former: Toward Cross-scale Boundary Modeling in Transformers

https://github.com/jeming-creater/hwa-unetr

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HWA-UNETR: Hierarchical Window Aggregate UNETR for 3D Multimodal Gastric Lesion Segmentation

https://github.com/jhl-det/fla-net

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Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos

https://github.com/jiayiliu-pku/ap2024

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Automated Lesion Segmentation in Whole-Body PET/CT in a multitracer setting

https://github.com/jiayiliu-pku/dc2024

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Enhancing Lesion Segmentation in PET/CT Imaging with Deep Learning and Advanced Data Preprocessing Techniques

https://github.com/jiazhang93/segmentation

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Whole-Body Lesion Segmentation in 18F-FDG PET/CT

https://github.com/jinghangli98/wmh_seg

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wmh_seg: Transformer based U-Net for Robust and Automatic White Matter Hyperintensity Segmentation across 1.5T, 3T and 7T

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