Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling

机译：基于自动形态计量和带重采样的惩罚线性判别分析的脑图像分类

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This paper presents a new data-driven classification pipeline for discriminating two groups of individuals based on the medical images of their brain. The algorithm combines deformation-based morphometry and penalised linear discriminant analysis with resampling. The method is based on sparse representation of the original brain images using deformation logarithms reflecting the differences in the brain in comparison to the normal template anatomy. The sparse data enables efficient data reduction and classification via the penalised linear discriminant analysis with resampling. The classification accuracy obtained in an experiment with magnetic resonance brain images of first episode schizophrenia patients and healthy controls is comparable to the related state-of-the-art studies.

机译：本文提出了一种新的数据驱动分类管道，用于基于他们大脑的医学图像来区分两组个体。该算法结合了基于变形的形态学和带重采样的惩罚线性判别分析。该方法基于原始大脑图像的稀疏表示，使用变形对数反映了与正常模板解剖结构相比大脑的差异。稀疏数据可以通过带有重采样的惩罚线性判别分析来进行有效的数据归约和分类。在首发精神分裂症患者和健康对照的磁共振脑图像实验中获得的分类准确性可与相关的最新研究相媲美。

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《Federated Conference on Computer Science and Information Systems》|2015年|263-268|共6页
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Janousova Eva; Schwarz Daniel; Montana Giovanni; Kasparek Tomas;
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biomedical MRI; brain; data reduction; image classification; image representation; image sampling; medical image processing; statistical analysis; automated morphometry; brain image classification; data reduction; data-driven classification pipeline; deformation logarithms; deformation-based morphometry; episode schizophrenia patients; magnetic resonance brain images; medical images; normal template anatomy; penalised linear discriminant analysis; sparse representation; Accuracy; Algorithm design and analysis; Brain; Classification algorithms; Diseases; Magnetic resonance imaging; Psychiatry;

机译：生物医学MRI;大脑;数据减少;图像分类;图像表示;图像采样;医学图像处理;统计分析;自动形态计量学;脑图像分类;数据缩减;数据驱动的分类管线;变形对数;基于变形的形态计量学;精神分裂症病人;磁共振脑图像;医学图像;正常模板解剖结构;分段线性判别分析;稀疏表示;准确性;算法设计和分析;脑;分类算法;疾病;磁共振成像;精神病学;

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1. Automated classification of multi-spectral MR images using Linear Discriminant Analysis. [J] . Lin GC, Wang WJ, Wang CM, Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society . 2010,第4期

机译：使用线性判别分析对多光谱MR图像进行自动分类。
2. Unsupervised tissue classification of brain MR images for voxel-based morphometry analysis [J] . Agnello Luca, Comelli Albert, Ardizzone Edoardo, International journal of imaging systems and technology . 2016,第2期

机译：基于体素形态分析的大脑MR图像的无监督组织分类
3. Brain morphometry of MR images for automated classification of first-episode schizophrenia [J] . Daniel Schwarz, Tomas Kasparek Information Fusion . 2014,第Null期

机译：MR图像的脑形态计量学用于首发精神分裂症的自动分类
4. Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling [C] . Janousova Eva, Schwarz Daniel, Montana Giovanni, Federated Conference on Computer Science and Information Systems . 2015

机译：基于自动形态学的脑图像分类与重新采样的惩罚线性判别分析
5. A COMPARISON OF SIX MODELS FOR PREDICTING CORPORATE BANKRUPTCY: MULTIPLE LINEAR REGRESSION ANALYSIS, MULTIPLE LINEAR DISCRIMINANT ANALYSIS, STEPWISE REGRESSION ANALYSIS, STEPWISE DISCRIMINANT ANALYSIS, MULTIPLE LINEAR REGRESSION ANALYSIS WITH RIDGE REGRESSION, AND MULTIPLE LINEAR DISCRIMINANT ANALYSIS WITH BIASED MINIMUM CHI-SQUARE RULE [D] . MAPP, JOHNNIE ALBERT. 1981

机译：六种预测公司破产的模型的比较：多个线性回归分析，多个线性判别分析，逐步回归分析，逐步判别分析，多个带岭点回归的线性回归分析，以及多个线性离散
6. A Classification Algorithm by Combination of Feature Decomposition and Kernel Discriminant Analysis (KDA) for Automatic MR Brain Image Classification and AD Diagnosis [O] . Farzaneh Elahifasaee, Fan Li, Ming Yang 2019

机译：结合特征分解和核判别分析（KDA）的自动MR脑图像分类和AD诊断的分类算法
7. Brain Image Classification Based on Automated Morphometry and Penalised Linear Discriminant Analysis with Resampling [O] . Eva Janoušová, Daniel Schwarz, Giovanni Montana, 2015

机译：基于自动形态学的脑图像分类与重新采样的惩罚线性判别分析

Brain image classification based on automated morphometry and penalised linear discriminant analysis with resampling

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