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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 201–225 of 640 papers

TitleStatusHype
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training—0
Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases—0
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation—0
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image SegmentationCode1
Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in TransformersCode1
CARE: A Large Scale CT Image Dataset and Clinical Applicable Benchmark Model for Rectal Cancer Segmentation—0
Large-kernel Attention for Efficient and Robust Brain Lesion SegmentationCode0
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation—0
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images—0
A hybrid approach for improving U-Net variants in medical image segmentation—0
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation DatasetsCode1
FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy ClassificationCode1
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentationCode2
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient NetworkCode1
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion SegmentationCode1
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation DatasetsCode1
Synchronous Image-Label Diffusion Probability Model with Application to Stroke Lesion Segmentation on Non-contrast CT—0
Boosting multiple sclerosis lesion segmentation through attention mechanismCode1
OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and DialogueCode1
Meta-Analysis of Transfer Learning for Segmentation of Brain Lesions—0
DAGrid: Directed Accumulator GridCode1
Multi-source adversarial transfer learning for ultrasound image segmentation with limited similarity—0
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images—0
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