Papers Skin Lesion Segmentation
“Skin Lesion Segmentation” 태그가 달린 논문 174편 · 필터 해제
MLFFM-SegDiff: A Multi-Level Feature Fusion Diffusion Model for Skin Lesion Segmentation
Skin lesion segmentation is a key task in computer-aided dermatological diagnosis, where accuracy directly impacts downstream analysis and disease classification. However, dermoscopic images are challenging due to blurre…
Medical Image SegmentationSkin Lesion SegmentationConcept Alignment Contrast and Long-Short Prompt Memory for Test-Time Adaptation of SAM3 in Medical Image Segmentation
Concept segmentation models like Segment Anything Model 3 (SAM3) show strong generalization on natural images, yet their performance degrades in medical imaging due to the domain gap caused by different imaging principle…
Medical Image SegmentationSkin Lesion SegmentationTest-time AdaptationPEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation
Automated segmentation of skin lesions using deep learning models for dermoscopic images can be very helpful in finding melanomas earlier than they would normally be detected. However, most deep learning methods availabl…
parameter-efficient fine-tuningSkin Lesion SegmentationPhase-Aware Wavelet-Based-Scattering Encoder-Decoder for Dense Predictions
Scattering transforms achieve Lipschitz stability and translation invariance, but dense prediction tasks require preserving spatial structure lost in global averaging. We propose Phase-Aware Scattering Encoder-Decoder, w…
Skin Lesion SegmentationImage DenoisingPatch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation
CNN- and Transformer-based architectures have achieved strong performance in medical image segmentation, but CNNs are limited in modeling long-range dependencies, while Transformers often suffer from quadratic computatio…
Medical Image SegmentationSkin Lesion SegmentationPolyp SegmentationUncertainty-Guided Dual-Domain Learning for Reliable Skin Lesion Segmentation
Accurate skin lesion segmentation is vital for dermoscopic Computer-Aided Diagnosis. However, visual ambiguity and morphological irregularity often defeat spatial modeling, necessitating multi-domain architectures. Exist…
Skin Lesion SegmentationMambaLiteUNet: Cross-Gated Adaptive Feature Fusion for Robust Skin Lesion Segmentation
Recent segmentation models have demonstrated promising efficiency by aggressively reducing parameter counts and computational complexity. However, these models often struggle to accurately delineate fine lesion boundarie…
Skin Lesion SegmentationDomain GeneralizationImage SegmentationRABC-Net: Reliability-Aware Annotation-Free Skin Lesion Segmentation for Low-Resource Dermoscopy
Pixel-level annotation is costly in low-resource dermoscopy. We present RABC-Net, a reliability-aware annotation-free segmentation system that combines pseudo-label reliability learning, restricted target-domain adaptati…
Skin Lesion SegmentationDomain AdaptationADP-FL-MedSeg: Adaptive Differential Privacy for Federated Medical Segmentation Across Diverse Modalities
Large volumes of medical data remain underutilized because centralizing distributed data is often infeasible due to strict privacy regulations and institutional constraints. In addition, models trained in centralized set…
Medical Image SegmentationBrain Tumor SegmentationSkin Lesion SegmentationFederated LearningExploring the Impact of Skin Color on Skin Lesion Segmentation
Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segmentation as a preprocessing step to delin…
Skin Lesion SegmentationIMA++: ISIC Archive Multi-Annotator Dermoscopic Skin Lesion Segmentation Dataset
Multi-annotator medical image segmentation is an important research problem, but requires annotated datasets that are expensive to collect. Dermoscopic skin lesion imaging allows human experts and AI systems to observe m…
Medical Image SegmentationSkin Lesion SegmentationUltraLBM-UNet: Ultralight Bidirectional Mamba-based Model for Skin Lesion Segmentation
Skin lesion segmentation is a crucial step in dermatology for guiding clinical decision-making. However, existing methods for accurate, robust, and resource-efficient lesion analysis have limitations, including low perfo…
Skin Lesion SegmentationKnowledge DistillationEffective Attention-Guided Multi-Scale Medical Network for Skin Lesion Segmentation
In the field of healthcare, precise skin lesion segmentation is crucial for the early detection and accurate diagnosis of skin diseases. Despite significant advances in deep learning for image processing, existing method…
Skin Lesion SegmentationWaveFuse-AL: Cyclical and Performance-Adaptive Multi-Strategy Active Learning for Medical Images
Active learning reduces annotation costs in medical imaging by strategically selecting the most informative samples for labeling. However, individual acquisition strategies often exhibit inconsistent behavior across diff…
Multi-class ClassificationSkin Lesion SegmentationBinary ClassificationPneumonia DetectionFocal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation
Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monitoring because it provides precise morphological and spatial information on ana…
Medical Image SegmentationSkin Lesion SegmentationConfidence-Weighted Semi-Supervised Learning for Skin Lesion Segmentation Using Hybrid CNN-Transformer Networks
Automated skin lesion segmentation through dermoscopic analysis is essential for early skin cancer detection, yet remains challenging due to limited annotated training data. We present MIRA-U, a semi-supervised framework…
Skin Lesion SegmentationMSA2-Net: Utilizing Self-Adaptive Convolution Module to Extract Multi-Scale Information in Medical Image Segmentation
The nnUNet segmentation framework adeptly adjusts most hyperparameters in training scripts automatically, but it overlooks the tuning of internal hyperparameters within the segmentation network itself, which constrains t…
Medical Image SegmentationSkin Lesion SegmentationDeep Skin Lesion Segmentation with Transformer-CNN Fusion: Toward Intelligent Skin Cancer Analysis
This paper proposes a high-precision semantic segmentation method based on an improved TransUNet architecture to address the challenges of complex lesion structures, blurred boundaries, and significant scale variations i…
Skin Lesion SegmentationSemantic SegmentationData AugmentationDermINO: Hybrid Pretraining for a Versatile Dermatology Foundation Model
Skin diseases impose a substantial burden on global healthcare systems, driven by their high prevalence (affecting up to 70% of the population), complex diagnostic processes, and a critical shortage of dermatologists in …
Skin Lesion SegmentationSelf-Supervised LearningFederated LearningWhat Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
Medical image segmentation exhibits intra- and inter-annotator variability due to ambiguous object boundaries, annotator preferences, expertise, and tools, among other factors. Lesions with ambiguous boundaries, e.g., sp…
Medical Image SegmentationSkin Lesion SegmentationMulti-Task Learning