基于临床可解释形态学特征的心脏电影MRI二尖瓣反流分类
Classification of Mitral Regurgitation from Cardiac Cine MRI using Clinically-Interpretable Morphological Features
AI总结：
针对心脏电影MRI评估二尖瓣反流（MR）时时间信息未被充分利用的问题，提出从重建二尖瓣环中自动提取4维形态学特征并结合MRMR特征选择与LDA、RF模型的方法，实现MR分类，相关代码开源。
摘要：
利用心脏MRI（尤其是电影MRI）评估二尖瓣反流（MR）因可用性广泛而成为一种有前景的技术。然而，临床电影MRI中可用的部分时间信息可能未被充分利用，因为这需要对不同心脏视图进行详细的时间分析。我们提出一种新方法来识别MR，该方法利用电影长轴（LAX）视图MRI从重建的二尖瓣环（MA）中自动提取4维（3D+时间）形态学特征。我们的特征提取包括定位MA插入点以推导重建的MA几何结构和位移，共得到187个候选特征。我们使用最小冗余最大相关性（MRMR）特征选择技术识别出25个最相关的二尖瓣特征。然后我们应用线性判别分析（LDA）和随机森林（RF）模型来确定MR的存在。在5折交叉验证分析中，LDA和RF均表现良好，准确率分别为0.72±0.05和0.73±0.09。该方法将被整合到一个自动工具中，通过结合手工特征和深度特征从电影MRI中识别瓣膜疾病。我们的工具将促进从常规心脏MRI扫描中诊断瓣膜疾病，且无需额外扫描或增加图像分析负担。所有代码已在开源基础上发布于：https://github.com/HenryOn2021/MA_Morphological_Features。
英文摘要：
The assessment of mitral regurgitation (MR) using cardiac MRI, particularly Cine MRI, is a promising technique due to its wide availability. However, some of the temporal information available in clinical Cine MRI may not be fully utilised, as it requires detailed temporal analysis across different cardiac views. We propose a new approach to identify MR which automatically extracts 4-dimensional (3D + Time) morphological features from the reconstructed mitral annulus (MA) using Cine long-axis (LAX) views MRI. Our feature extraction involves locating the MA insertion points to derive the reconstructed MA geometry and displacements, resulting in a total of 187 candidate features. We identify the 25 most relevant mitral valve features using minimum-redundancy maximum-relevance (MRMR) feature selection technique. We then apply linear discriminant analysis (LDA) and random forest (RF) model to determine the presence of MR. Both LDA and RF demonstrate good performance, with accuracies of 0.72+/-0.05 and 0.73+/-0.09, respectively, in a 5-fold cross-validation analysis. This approach will be incorporated in an automatic tool to identify valvular diseases from Cine MRI by integrating both handcrafted and deep features. Our tool will facilitate the diagnosis of valvular disease from conventional cardiac MRI scans with no additional scanning or image analysis penalty. All code is made available on an open-source basis at: https://github.com/HenryOn2021/MA_Morphological_Features.
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。
