Machine Learning using Medical Images in Dementia and its Problems

Abstract

Magnetic resonance imaging (MRI) T1-weighted images are often used in the diagnosis of diseases such as brain degeneration because MRI has superior contrast of soft tissue. Although the clinical use of MRI has traditionally been limited to visual evaluation by radiologists, but recent advances in image analysis techniques possible to automatically quantitatively evaluate brain volume voxel by voxel and within anatomical regions of interest. This has led to many reported applications in machine learning using a hues amount of MRI data sets. However, medical imaging, a type of clinical data, involves various problems caused by their clinical backgrounds and imaging scanner. In this paper, we focus on dementia and structural MRI, and introduce the analysis methods and their applications to machine learning, as well as the problems that exist in machine learning using medical images.