Automated Diagnostic Model Based on Isoline Map Analysis of Myocardial Tissue Structure

机译：基于等值线图分析的心肌组织结构自动诊断模型

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Diagnostics of heart diseases by myocardial tissue structure analysis is very important since there exist several cardiac pathologies, indistinguishable by other symptoms. The most similar existing methods for automatic diagnostics by myocardium analysis in CT images are based only on intensity histogram features. In this work we describe the proposed method that uses isoline map-based features. We use real MSCT images with manually segmented LV myocardium to compare the existing algorithm and variations of the proposed algorithm, utilizing different strategies of isoline map construction (single- and double-level maps) for further computation of features, feature selection methods (Information Gain and Chi-squared test) and algorithms for binary classification of slice images into normal/abnormal classes (SVM and Random Forest). All considered types of isoline map-based diagnostic models demonstrate better results than histogram-based model. The best diagnostic models achieve 99.7% ROC AUC, 96.7% F-score and 0.7% false negative rate.

机译：通过心肌组织结构分析对心脏病的诊断非常重要，因为存在几种心脏病，其他症状无法区分。通过CT图像中的心肌分析进行自动诊断的现有方法中，最相似的方法仅基于强度直方图特征。在这项工作中，我们描述了使用基于等值线图的特征的建议方法。我们使用带有手动分段LV心肌的真实MSCT图像来比较现有算法和该算法的变体，利用等值线图构造（单层和双层图）的不同策略进一步计算特征，特征选择方法（信息增益）和卡方检验）和将切片图像按正常/异常类别（SVM和随机森林）进行二进制分类的算法。与基于直方图的模型相比，所有考虑的基于等值线图的诊断模型类型均显示出更好的结果。最好的诊断模型可实现99.7％的ROC AUC，96.7％的F评分和0.7％的假阴性率。

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《International joint conference on computational intelligence》|2017年|221-238|共18页
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Olga V. Senyukova; Danuta S. Brotikovskaya; Svetlana G. Gorokhova; Ekaterina S. Tebenkova;
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Automated heart disease diagnostics; Heart tissue analysis; LV myocardium; Isoline map; Supervised machine learning; Multispiral computed tomography;

机译：自动化心脏病诊断;心脏组织分析;左心室心肌;等值线图;有监督的机器学习;多螺旋CT;

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机译：肥厚性心肌病心肌细胞的MRI Native T1和T2映射：在结构变化之前表现出组织重塑
2. Quantitative Analysis of Connective Tissue Matrix Structure during Myocardial Remodeling [J] . L. T. Smoluk, A. T. Smoluk, Y. L. Protsenko Biophysics . 2014,第5期

机译：心肌重塑过程中结缔组织基质结构的定量分析
3. Multi-channel, convolutional attention based neural model for automated diagnostic coding of unstructured patient discharge summaries [J] . Veena Mayya, Sowmya Kamath S., Gokul S. Krishnan, Future generation computer systems . 2021,第May期

机译：基于多通道，基于卷积注意的神经模型，用于非结构化患者放电摘要的自动诊断编码
4. Automated Diagnostic Model Based on Isoline Map Analysis of Myocardial Tissue Structure [C] . Olga V. Senyukova, Danuta S. Brotikovskaya, Svetlana G. Gorokhova, International joint conference on computational intelligence . 2019

机译：基于ISOLINE地图分析的自动化诊断模型
5. An Active Texture-based Atlas for Automated Mapping of Structures and Markers Across Brains [D] . Chen, Yuncong. 2018

机译：基于活动纹理的地图集，可自动绘制大脑中的结构和标记
6. Automated quantification of myocardial tissue characteristics from native T1 mapping using neural networks with uncertainty-based quality-control [O] . Esther Puyol-Antón, Bram Ruijsink, Christian F. Baumgartner, 2020

机译：利用神经网络与基于不确定性的质量控制的神经网络自动定量来自天然T1映射的心肌组织特征
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8. Automated Synthesis of Prediction Models for Neural Network Based Myocardial Infarction Classifiers. [R] . Lopez, J. A., Nugent, C. D., Black, N. D., 2001

机译：基于神经网络的心肌梗死分类器预测模型的自动综合。

Automated Diagnostic Model Based on Isoline Map Analysis of Myocardial Tissue Structure

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