IntelliCardiac：一个面向心脏图像分割与分类的智能平台
IntelliCardiac: An Intelligent Platform for Cardiac Image Segmentation and Classification
AI总结：
IntelliCardiac 是一个基于 Web 的 4D 心脏图像智能平台，结合深度学习分割模型与两阶段分类流程，在 ACDC 数据集上实现 92.6% 分割准确率和 98% 五类疾病分类准确率，用于临床决策辅助。
摘要：
对心脏成像数据进行精确且有效的处理，对于心血管疾病的识别与管理至关重要。我们提出了 IntelliCardiac，一个基于 Web 的综合医学图像处理平台，用于 4D 心脏图像的自动分割和疾病分类，其 AI 模型在公开可用的 ACDC 数据集上训练。该系统面向患者、心脏病专家和医疗保健专业人员，提供直观界面，并利用深度学习模型识别关键心脏结构并对心脏疾病进行分类。该系统支持对右心室、左心室以及心肌进行分析，然后将患者的心脏图像分类为五种诊断类别：扩张型心肌病、心肌梗死、肥厚型心肌病、右心室异常和无疾病。IntelliCardiac 将基于深度学习的分割模型与两阶段分类流程相结合。分割模块的总体准确率达到 92.6%。分类模块基于从分割出的心脏结构中提取的特征进行训练，在五个类别上实现了 98% 的准确率。这些结果超过了现有同时整合分割与分类模型的最先进方法的性能。IntelliCardiac 支持实时可视化、工作流集成和 AI 辅助诊断，作为一种可扩展且准确的工具，在心脏成像和诊断的临床决策辅助方面具有巨大潜力。
英文摘要：
Precise and effective processing of cardiac imaging data is critical for the identification and management of the cardiovascular diseases. We introduce IntelliCardiac, a comprehensive, web-based medical image processing platform for the automatic segmentation of 4D cardiac images and disease classification, utilizing an AI model trained on the publicly accessible ACDC dataset. The system, intended for patients, cardiologists, and healthcare professionals, offers an intuitive interface and uses deep learning models to identify essential heart structures and categorize cardiac diseases. The system supports analysis of both the right and left ventricles as well as myocardium, and then classifies patient's cardiac images into five diagnostic categories: dilated cardiomyopathy, myocardial infarction, hypertrophic cardiomyopathy, right ventricular abnormality, and no disease. IntelliCardiac combines a deep learning-based segmentation model with a two-step classification pipeline. The segmentation module gains an overall accuracy of 92.6%. The classification module, trained on characteristics taken from segmented heart structures, achieves 98% accuracy in five categories. These results exceed the performance of the existing state-of-the-art methods that integrate both segmentation and classification models. IntelliCardiac, which supports real-time visualization, workflow integration, and AI-assisted diagnostics, has great potential as a scalable, accurate tool for clinical decision assistance in cardiac imaging and diagnosis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
