Papers Skin Lesion Classification
“Skin Lesion Classification” 태그가 달린 논문 154편 · 필터 해제
Compositional Reward Models for Conditional Medical Image Generation
Acquiring high quality annotated medical image data is critical for training deep learning models; however, annotation is expensive, time consuming, and requires domain expertise. Conditional diffusion models, such as Co…
Skin Lesion ClassificationMedical Image GenerationReinforcement LearningCell SegmentationConformal Risk Minimization for Semi-Supervised Domain Adaptation via Optimal Transport
In high-stakes healthcare applications, machine learning models are frequently trained on data from one patient population and deployed on another, creating a distribution shift that degrades both accuracy and reliabilit…
Skin Lesion ClassificationDomain AdaptationGeometry-Aware Superpixel Graph Transformer with Metadata for Skin Lesion Classification
Automated skin cancer classification from dermoscopic images remains challenging due to heterogeneous lesion structure, strong intra-class variability, and subtle visual differences between benign and malignant cases. Ex…
Skin Lesion ClassificationSkin Cancer ClassificationMultimodal ReasoningGraph LearningEffect of Demographic Bias on Skin Lesion Classification
In this study, we evaluate the performance of skin lesion classification using ResNet-based convolutional models, focusing on the impact of demographic bias in training data, particularly variations in patient sex and ag…
Skin Lesion ClassificationSynthetic Data Generation for Long-Tail Medical Image Classification: A Case Study in Skin Lesions
Long-tailed class distributions are pervasive in multi-class medical datasets and pose significant challenges for deep learning models which typically underperform on tail classes with limited samples. This limitation is…
Medical Image ClassificationSkin Lesion ClassificationSynthetic Data GenerationData AugmentationJI-ADF: Joint-Individual Learning with Adaptive Decision Fusion for Multimodal Skin Lesion Classification
Skin lesion classification is essential for early dermatological diagnosis, yet many existing computer-aided systems rely primarily on dermoscopic images and underutilize the multimodal evidence routinely available in cl…
Skin Lesion ClassificationRepresentation LearningDermaFlux: Synthetic Skin Lesion Generation with Rectified Flows for Enhanced Image Classification
Despite recent advances in deep generative modeling, skin lesion classification systems remain constrained by the limited availability of large, diverse, and well-annotated clinical datasets, resulting in class imbalance…
Skin Lesion ClassificationBinary ClassificationImage ClassificationDerMAE: Improving skin lesion classification through conditioned latent diffusion and MAE distillation
Skin lesion classification datasets often suffer from severe class imbalance, with malignant cases significantly underrepresented, leading to biased decision boundaries during deep learning training. We address this chal…
Skin Lesion ClassificationKnowledge DistillationContrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions
Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leading to performance degradation when deployed in clinical settings. We inv…
Skin Lesion ClassificationDomain AdaptationA Hierarchical Benchmark of Foundation Models for Dermatology
Foundation models have transformed medical image analysis by providing robust feature representations that reduce the need for large-scale task-specific training. However, current benchmarks in dermatology often reduce t…
Skin Lesion ClassificationBinary ClassificationIntegrating Color Histogram Analysis and Convolutional Neural Network for Skin Lesion Classification
The color of skin lesions is an important diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue …
Skin Lesion ClassificationA Deep Learning Approach for Automated Skin Lesion Diagnosis with Explainable AI
Skin cancer is also one of the most common and dangerous types of cancer in the world that requires timely and precise diagnosis. In this paper, a deep-learning architecture of the multi-class skin lesion classification …
Skin Lesion ClassificationData AugmentationSkin Lesion Classification Using a Soft Voting Ensemble of Convolutional Neural Networks
Skin cancer can be identified by dermoscopic examination and ocular inspection, but early detection significantly increases survival chances. Artificial intelligence (AI), using annotated skin images and Convolutional Ne…
Skin Lesion ClassificationSkin Cancer ClassificationImage AugmentationTransfer LearningMelanomaNet: Explainable Deep Learning for Skin Lesion Classification
Automated skin lesion classification using deep learning has shown remarkable accuracy, yet clinical adoption remains limited due to the "black box" nature of these models. We present MelanomaNet, an explainable deep lea…
Skin Lesion ClassificationMitigating Individual Skin Tone Bias in Skin Lesion Classification through Distribution-Aware Reweighting
Skin color has historically been a focal point of discrimination, yet fairness research in machine learning for medical imaging often relies on coarse subgroup categories, overlooking individual-level variations. Such gr…
Skin Lesion ClassificationDensity EstimationSkewness-Guided Pruning of Multimodal Swin Transformers for Federated Skin Lesion Classification on Edge Devices
In recent years, high-performance computer vision models have achieved remarkable success in medical imaging, with some skin lesion classification systems even surpassing dermatology specialists in diagnostic accuracy. H…
Skin Lesion ClassificationFederated LearningModel CompressionAI-Powered Early Detection of Critical Diseases using Image Processing and Audio Analysis
Early diagnosis of critical diseases can significantly improve patient survival and reduce treatment costs. However, existing diagnostic techniques are often costly, invasive, and inaccessible in low-resource regions. Th…
Skin Lesion ClassificationTowards Explainable Skin Cancer Classification: A Dual-Network Attention Model with Lesion Segmentation and Clinical Metadata Fusion
Skin cancer is a life-threatening disease where early detection significantly improves patient outcomes. Automated diagnosis from dermoscopic images is challenging due to high intra-class variability and subtle inter-cla…
Skin Lesion ClassificationSkin Cancer ClassificationLesion SegmentationA Multi-Task Deep Learning Framework for Skin Lesion Classification, ABCDE Feature Quantification, and Evolution Simulation
Early detection of melanoma has grown to be essential because it significantly improves survival rates, but automated analysis of skin lesions still remains challenging. ABCDE, which stands for Asymmetry, Border irregula…
Skin Lesion ClassificationSkin Lesion Classification Based on ResNet-50 Enhanced With Adaptive Spatial Feature Fusion
Skin cancer classification is challenging due to high inter-class similarity, intra-class variability, and artifacts in dermoscopic images. To address these issues, we propose an improved ResNet-50 with Adaptive Spatial …
Skin Lesion ClassificationSkin Cancer Classification