Lesion Segmentation
208 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
DigestPath
ISIC 2018 Task 1
ISIC 2017 Task 1
FGADR
University of Waterloo skin cancer database
ISIC 2018 Task 3
Latest papers with no code
Multi-target and multi-stage liver lesion segmentation and detection in multi-phase computed tomography scans
Although this approach utilizes information from all the phases and outperform single-phase segmentation networks, we demonstrate that their performance is not optimal and can be further improved by incorporating the learning from models trained on each single-phase individually.
Integrating Mamba Sequence Model and Hierarchical Upsampling Network for Accurate Semantic Segmentation of Multiple Sclerosis Legion
Integrating components from convolutional neural networks and state space models in medical image segmentation presents a compelling approach to enhance accuracy and efficiency.
Innovative Quantitative Analysis for Disease Progression Assessment in Familial Cerebral Cavernous Malformations
To alleviate this problem, we propose a quantitative statistical framework for FCCM, comprising an efficient annotation module, an FCCM lesion segmentation module, and an FCCM lesion quantitative statistics module.
P-Count: Persistence-based Counting of White Matter Hyperintensities in Brain MRI
White matter hyperintensities (WMH) are a hallmark of cerebrovascular disease and multiple sclerosis.
A Spatial-Temporal Progressive Fusion Network for Breast Lesion Segmentation in Ultrasound Videos
The main challenge for ultrasound video-based breast lesion segmentation is how to exploit the lesion cues of both intra-frame and inter-frame simultaneously.
Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation
In machine learning larger databases are usually associated with higher classification accuracy due to better generalization.
Mask-Enhanced Segment Anything Model for Tumor Lesion Semantic Segmentation
Tumor lesion segmentation on CT or MRI images plays a critical role in cancer diagnosis and treatment planning.
Multi-organ Self-supervised Contrastive Learning for Breast Lesion Segmentation
Self-supervised learning has proven to be an effective way to learn representations in domains where annotated labels are scarce, such as medical imaging.
wmh_seg: Transformer based U-Net for Robust and Automatic White Matter Hyperintensity Segmentation across 1.5T, 3T and 7T
Despite the unique inhomogeneity artifacts on ultra-high field MR images, our model still offers robust and stable segmentation on 7T FLAIR images.
Is Two-shot All You Need? A Label-efficient Approach for Video Segmentation in Breast Ultrasound
Breast lesion segmentation from breast ultrasound (BUS) videos could assist in early diagnosis and treatment.
