Yucca: A Deep Learning Framework For Medical Image Analysis
Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-friendliness. To address these challenges, we introduce Yucca, an open-source AI framework available at https://github.com/Sllambias/yucca, designed specifically for medical imaging applications and built on PyTorch and PyTorch Lightning. Yucca features a three-tiered architecture: Functional, Modules, and Pipeline, providing a comprehensive and customizable solution. Evaluated across diverse tasks such as cerebral microbleeds detection, white matter hyperintensity segmentation, and hippocampus segmentation, Yucca achieves state-of-the-art results, demonstrating its robustness and versatility. Yucca offers a powerful, flexible, and user-friendly platform for medical image analysis, inviting community contributions to advance its capabilities and impact.
Code (1)
Tasks
Deep LearningHippocampusMedical Image AnalysisSegmentationSimilar Papers 제목 키워드 기반
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of eXpl…
Decision MakingDeep LearningExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)+1Parallel Medical Imaging for Intelligent Medical Image Analysis: Concepts, Methods, and Applications
There has been much progress in data-driven artificial intelligence technology for medical image analysis in the last decades. However, it still remains challenging due to its distinctive complexity of acquiring and anno…
DiagnosticMedical Image AnalysisA Review of Causality for Learning Algorithms in Medical Image Analysis
Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost…
BIG-bench Machine LearningMedical Image AnalysisTranslationRELICT: A Replica Detection Framework for Medical Image Generation
Despite the potential of synthetic medical data for augmenting and improving the generalizability of deep learning models, memorization in generative models can lead to unintended leakage of sensitive patient information…
Image GenerationMedical Image GenerationMemorizationSurvey on Adversarial Attack and Defense for Medical Image Analysis: Methods and Challenges
Deep learning techniques have achieved superior performance in computer-aided medical image analysis, yet they are still vulnerable to imperceptible adversarial attacks, resulting in potential misdiagnosis in clinical pr…
Adversarial AttackMedical DiagnosisMedical Image AnalysisSurvey