Papers Lesion Classification
“Lesion Classification” 태그가 달린 논문 189편 · 필터 해제
Uncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation
Accurate and reliable skin cancer diagnosis is critical for early treatment and improved patient outcomes. Deep learning (DL) models have shown promise in automating skin cancer classification, but their performance can …
Cancer ClassificationLesion ClassificationMedical DiagnosisSkin Cancer Classification+4Skin Lesion Phenotyping via Nested Multi-modal Contrastive Learning
We introduce SLIMP (Skin Lesion Image-Metadata Pre-training) for learning rich representations of skin lesions through a novel nested contrastive learning approach that captures complex relationships between images and m…
Contrastive LearningLesion ClassificationSkin Lesion ClassificationFusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification
Accurate classification of skin lesions from dermatoscopic images is essential for diagnosis and treatment of skin cancer. In this study, we investigate the utility of a dermatology-specific foundation model, PanDerm, in…
Classificationimage-classificationImage ClassificationLesion Classification+1Domain Adaptive Skin Lesion Classification via Conformal Ensemble of Vision Transformers
Exploring the trustworthiness of deep learning models is crucial, especially in critical domains such as medical imaging decision support systems. Conformal prediction has emerged as a rigorous means of providing deep le…
Conformal PredictionDomain AdaptationEnsemble Learningimage-classification+4A Vision-Language Model for Focal Liver Lesion Classification
Accurate classification of focal liver lesions is crucial for diagnosis and treatment in hepatology. However, traditional supervised deep learning models depend on large-scale annotated datasets, which are often limited …
Language ModelingLanguage ModellingLesion ClassificationA Lightweight U-Net Model for Accurate Skin Lesion Segmentation
In this paper, a new lightweight U-Net deep learning-based neural network designed for the segmentation of skin lesions is proposed. Segmentation of skin lesions is the most critical step in computer-aided dermatology di…
Lesion ClassificationLesion SegmentationSensitivitySkin Lesion Classification+1Conformal uncertainty quantification to evaluate predictive fairness of foundation AI model for skin lesion classes across patient demographics
Deep learning based diagnostic AI systems based on medical images are starting to provide similar performance as human experts. However these data hungry complex systems are inherently black boxes and therefore slow to b…
DiagnosticFairnessLesion ClassificationSkin Lesion Classification+1Unpaired Translation of Chest X-ray Images for Lung Opacity Diagnosis via Adaptive Activation Masks and Cross-Domain Alignment
Chest X-ray radiographs (CXRs) play a pivotal role in diagnosing and monitoring cardiopulmonary diseases. However, lung opac- ities in CXRs frequently obscure anatomical structures, impeding clear identification of lung …
Lesion ClassificationSensitivityTranslationFedSKD: Aggregation-free Model-heterogeneous Federated Learning using Multi-dimensional Similarity Knowledge Distillation
Federated learning (FL) enables privacy-preserving collaborative model training without direct data sharing. Model-heterogeneous FL (MHFL) extends this paradigm by allowing clients to train personalized models with heter…
Federated LearningKnowledge DistillationLesion ClassificationPrivacy Preserving+2Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework
Data-driven AI is establishing itself at the center of evidence-based medicine. However, reports of shortcomings and unexpected behavior are growing due to AI's reliance on association-based learning. A major reason for …
AttributeLesion ClassificationMortality PredictionSkin Lesion ClassificationSubgroup Performance Analysis in Hidden Stratifications
Machine learning (ML) models may suffer from significant performance disparities between patient groups. Identifying such disparities by monitoring performance at a granular level is crucial for safely deploying ML to ea…
Lesion ClassificationSkin Lesion ClassificationSubgroup DiscoveryRevisit the Stability of Vanilla Federated Learning Under Diverse Conditions
Federated Learning (FL) is a distributed machine learning paradigm enabling collaborative model training across decentralized clients while preserving data privacy. In this paper, we revisit the stability of the vanilla …
ClassificationFederated LearningLesion ClassificationSkin Lesion ClassificationDeep learning and classical computer vision techniques in medical image analysis: Case studies on brain MRI tissue segmentation, lung CT COPD registration, and skin lesion classification
Medical imaging spans diverse tasks and modalities which play a pivotal role in disease diagnosis, treatment planning, and monitoring. This study presents a novel exploration, being the first to systematically evaluate s…
Image RegistrationLesion ClassificationMedical Image AnalysisSkin Lesion ClassificationGS-TransUNet: Integrated 2D Gaussian Splatting and Transformer UNet for Accurate Skin Lesion Analysis
We can achieve fast and consistent early skin cancer detection with recent developments in computer vision and deep learning techniques. However, the existing skin lesion segmentation and classification prediction models…
ClassificationDiagnosticLesion ClassificationLesion Segmentation+4Spatio-temporal collaborative multiple-stream transformer network for liver lesion classification on multiple-sequence magnetic resonance imaging
Accurate identification of focal liver lesions is essential for determining the appropriate therapeutic approach in clinical practice. Magnetic resonance imaging (MRI) is a valuable technology for precise classification,…
DiagnosticLesion ClassificationHierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification
Explainability is a highly demanded requirement for applications in high-risk areas such as medicine. Vision Transformers have mainly been limited to attention extraction to provide insight into the model's reasoning. Ou…
image-classificationImage ClassificationLesion ClassificationMedical Image Classification+1Deep Task-Based Beamforming and Channel Data Augmentations for Enhanced Ultrasound Imaging
This paper introduces a deep learning (DL)-based framework for task-based ultrasound (US) beamforming, aiming to enhance clinical outcomes by integrating specific clinical tasks directly into the beamforming process. Tas…
Lesion ClassificationProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer
Prostate cancer, a growing global health concern, necessitates precise diagnostic tools, with Magnetic Resonance Imaging (MRI) offering high-resolution soft tissue imaging that significantly enhances diagnostic accuracy.…
AttributeDiagnosticImage GenerationLesion Classification+1A Cascaded Dilated Convolution Approach for Mpox Lesion Classification
The global outbreak of the Mpox virus, classified as a Public Health Emergency of International Concern (PHEIC) by the World Health Organization, presents significant diagnostic challenges due to its visual similarity to…
Computational EfficiencyDiagnosticLesion ClassificationSkin Lesion ClassificationEnhancing the Generalization Capability of Skin Lesion Classification Models with Active Domain Adaptation Methods
We propose a method to improve the generalization ability of skin lesion classification models by combining self-supervised learning (SSL), unsupervised domain adaptation (UDA), and active domain adaptation (ADA). The ma…
Domain AdaptationLesion ClassificationSelf-Supervised LearningSkin Lesion Classification+1