Local-Global Description of Digital Images for Detection and Analysis of Medical Features

Abstract

This paper presents two descriptors to tackle the existing problems
in medical imaging by providing more information to describe
different textural structures of digital images. The proposed global
and local descriptors can provide more accurate analysis of medical
features by using hybrid concatenation approach. Several
mathematical models in the form of local and global descriptors have
been developed and used in the computation and analysis of medical
problems. The experimental results showed that both local and
global features are very useful in detection and analysis of
biomedical features. The results also indicate that the global
descriptor outperforms the earlier approaches and demonstrates
high discriminating power and robustness of combined features for
accurate classification of CT images.