A new image-based immersive tool for dementia diagnosis using pairwise ranking and learning

Abstract

Dementia disease is globally acknowledged as one of the most severe non-communicable diseases nowadays. Identifying different stages of dementia disease is significant in its later treatment for delaying the onset and progression of the disease. Among diverse types of tools utilized in dementia disease diagnosis, brain scanning is generally accepted as an effective and affordable way at present. There are several kinds of medical images incorporated in contemporary dementia studies, and magnetic resonance images receives vast popularity. In this study, arterial spin labeling, an emerging perfusion functional-magnetic resonance imaging technique, is adopted in a newly proposed image-based immersive tool for dementia disease diagnosis. Novel pairwise ranking and learning techniques based on a new continuous and differentiable surrogated Kendall-Tau rank correlation coefficient is proposed to realize the immersive tool. Extensive experiments based on a database composed of images acquired from 350 demented patients are carried out with several popular pattern recognition diagnosis tools being compared. Their results undergo rigorous and comprehensive statistical analysis, and the superiority of the newly proposed image-based immersive tool in dementia disease diagnosis has been demonstrated.