科研成果
科研成果

脑科学中心通过机器学习在阿尔兹海默症脑MR影像中提取脑病理年龄的研究取得进展


脑科学中心前期已经从AD的MR影像中提取出相关解剖结构特征,引入不同程度AD的年龄偏差不同的实际,建立脑病理年龄回归模型,并成功提取出脑病理年龄特征。所提取的脑病理年龄与类别标签的相关性相比于传统的脑年龄检测和实际年龄与类别标签的相关性都有显著提高。脑病理年龄的提取有助于辅助医生对于AD的诊断,提高AD的诊断准确率。相关研究已经发表在BioMedical Engineering Online。该课题由李勇明老师指导刘玉川同学主要完成。

Dependency criterion based brain pathological age estimation of Alzheimer’s disease patients with MR scans

Yongming Li*,Yuchuan Liu,Pin Wang,Jie Wang,Sha Xu,MingguoQiu

Objectives:Traditional age estimation methods are based on the idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to accelerated brain aging.Materials and methods:This paper considers this deviation and obtains it by maximizing the correlation between the estimated brain age and the class label rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to the prior knowledge. Secondly, use the support vector regression as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the correlation criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age.Results:The experimental results showed that the separability of the samples was apparently improved. For normal control- Alzheimer’s disease (NC-AD), normal control- mild cognition impairment (NC-MCI), and mild cognition impairment - Alzheimer’s disease (MCI-AD), the average improvements were 0.164(31.66%), 0.1284(34.29%), and 0.0206(7.1%), respectively. For NC-MCI-AD, the average improvement was 0.2002(50.39%). The estimated brain pathological age could be not only more helpful for the classification of AD but also more precisely reflect the accelerated brain aging.Conclusion:In conclusion, this paper proposes a new kind of brain age – brain pathological age and offers an estimation method for it that can distinguish different states of AD, thereby better reflectingaccelerated brain aging.Besides, the brain pathological age is most helpful for feature reduction, thereby simplifying the relevant c

其他成果
    朱峰教授组在Nucleic Acids Research发表文章!
    脑科学中心通过机器学习在阿尔兹海默症脑MR影像中提取脑病理年龄的研究取得进展