Lesion Segmentation
207 papers with code • 10 benchmarks • 13 datasets
Lesion segmentation is the task of segmenting out lesions from other objects in medical based images.
( Image credit: D-UNet )
Benchmarks
These leaderboards are used to track progress in Lesion Segmentation
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Libraries
Use these libraries to find Lesion Segmentation models and implementationsDatasets
HAM10000
ISIC 2018 Task 1
DigestPath
ISIC 2017 Task 1
FGADR
University of Waterloo skin cancer database
ISIC 2018 Task 3
Latest papers
Skin Lesion Segmentation Improved by Transformer-based Networks with Inter-scale Dependency Modeling
saniaesk/skin-lesion-segmentation
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As a result, we propose a U-shaped hierarchical Transformer-based structure for skin lesion segmentation and an Inter-scale Context Fusion (ISCF) method that uses attention correlations in each stage of the encoder to adaptively combine the contexts from each stage to mitigate semantic gaps.
UCM-Net: A Lightweight and Efficient Solution for Skin Lesion Segmentation using MLP and CNN
Skin cancer poses a significant public health challenge, necessitating efficient diagnostic tools.
SSG2: A new modelling paradigm for semantic segmentation
feevos/ssg2
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By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates.
BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision
Brain stroke has become a significant burden on global health and thus we need remedies and prevention strategies to overcome this challenge.
AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical Knowledge
When delineating lesions from medical images, a human expert can always keep in mind the anatomical structure behind the voxels.
Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos
jhl-det/fla-net
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We also devise a localization-based contrastive loss to reduce the lesion location distance between neighboring video frames within the same video and enlarge the location distances between frames from different ultrasound videos.
Generalized Dice Focal Loss trained 3D Residual UNet for Automated Lesion Segmentation in Whole-Body FDG PET/CT Images
These lesions can be found in various parts of the body, often close to healthy organs that also show significant uptake.
A Localization-to-Segmentation Framework for Automatic Tumor Segmentation in Whole-Body PET/CT Images
medcai/l2snet
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However, precise tumor segmentation is challenging due to the small size of many tumors and the similarity of high-uptake normal areas to the tumor regions.
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs
In this work, we propose a novel unsupervised Skin Lesion sEgmentation framework based on structural entropy and isolation forest outlier Detection, namely SLED.
INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses
In this study, we propose a novel deep neural network (DNN), entitled InceptNet, in the scope of medical image processing, for early disease detection and segmentation of medical images in order to enhance precision and performance.
