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Lesion Segmentation

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

( Image credit: D-UNet )

Papers

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Showing 126–150 of 640 papers

TitleStatusHype
Fuzzy Information Seeded Region Growing for Automated Lesions After Stroke Segmentation in MR Brain ImagesCode1
Lightweight Model For The Prediction of COVID-19 Through The Detection And Segmentation of Lesions in Chest CT ScansCode1
Bi-Directional ConvLSTM U-Net with Densley Connected ConvolutionsCode1
ASC-Net : Adversarial-based Selective Network for Unsupervised Anomaly SegmentationCode1
Constrained unsupervised anomaly segmentationCode1
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentationCode1
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion SegmentationCode1
Diffusion Models for Implicit Image Segmentation EnsemblesCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
Boundary-aware Transformers for Skin Lesion SegmentationCode1
Boundary loss for highly unbalanced segmentationCode1
ASP-VMUNet: Atrous Shifted Parallel Vision Mamba U-Net for Skin Lesion SegmentationCode1
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image SegmentationCode1
A Region of Interest Focused Triple UNet Architecture for Skin Lesion Segmentation—0
Bag of Tricks for Developing Diabetic Retinopathy Analysis Framework to Overcome Data Scarcity—0
A Progressively-trained Scale-invariant and Boundary-aware Deep Neural Network for the Automatic 3D Segmentation of Lung Lesions—0
AutoPETIII: The Tracer Frontier. What Frontier?—0
Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis—0
AutoPET III Challenge: Tumor Lesion Segmentation using ResEnc-Model Ensemble—0
AutoPET III Challenge: PET/CT Semantic Segmentation—0
Application of the nnU-Net for automatic segmentation of lung lesion on CT images, and implication on radiomic models—0
AutoPET Challenge: Tumour Synthesis for Data Augmentation—0
Accurate and Robust Lesion RECIST Diameter Prediction and Segmentation with Transformers—0
3DPX: Single Panoramic X-ray Analysis Guided by 3D Oral Structure Reconstruction—0
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