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Lesion Segmentation
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Autopet Challenge 2023: nnUNet-based whole-body 3D PET-CT Tumour Segmentation
USL-Net: Uncertainty Self-Learning Network for Unsupervised Skin Lesion Segmentation
A mirror-Unet architecture for PET/CT lesion segmentation
Auto-Lesion Segmentation with a Novel Intensity Dark Channel Prior for COVID-19 Detection
A Localization-to-Segmentation Framework for Automatic Tumor Segmentation in Whole-Body PET/CT Images
Punctate White Matter Lesion Segmentation in Preterm Infants Powered by Counterfactually Generative Learning
Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications
Unsupervised Skin Lesion Segmentation via Structural Entropy Minimization on Multi-Scale Superpixel Graphs
INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses
Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in Multiple Anatomical Locations
Channel Attention Separable Convolution Network for Skin Lesion Segmentation
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training
Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection
Attention-based CT Scan Interpolation for Lesion Segmentation of Colorectal Liver Metastases
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation
Unlocking Fine-Grained Details with Wavelet-based High-Frequency Enhancement in Transformers
CARE: A Large Scale CT Image Dataset and Clinical Applicable Benchmark Model for Rectal Cancer Segmentation
Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images
Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images
A hybrid approach for improving U-Net variants in medical image segmentation
AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets
FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network
EGE-UNet: an Efficient Group Enhanced UNet for skin lesion segmentation
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
Synchronous Image-Label Diffusion Probability Model with Application to Stroke Lesion Segmentation on Non-contrast CT
OphGLM: Training an Ophthalmology Large Language-and-Vision Assistant based on Instructions and Dialogue
Meta-Analysis of Transfer Learning for Segmentation of Brain Lesions
DAGrid: Directed Accumulator Grid
Scale-aware Super-resolution Network with Dual Affinity Learning for Lesion Segmentation from Medical Images
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