Improved Automatic Anatomic Location Identification Approach and CBR-Based Treatment Management System for Pediatric Foreign Body Aspiration

Abstract

In general, the diagnosis and treatment planning of pediatric foreign body aspiration is done by medical experts with experience and uncertain clinical data of the patients, which makes the diagnosis a more approximate and time-consuming process. Foreign body diagnostic information requires the evidence such as size, shape, and location classification of the aspired foreign body. This evidence identification process requires the knowledge of human expertise to achieve accuracy in classification. The aim of the proposed work is to improve the performance of automatic anatomic location identification approach (AALIA) and to develop a reasoning-based systematic approach for pediatric foreign body aspiration treatment management. A CBR-based treatment management system is proposed for standardizing the pediatric foreign body aspiration treatment management process. The proposed approach considered a sample set of foreign body-aspired pediatric radiography images for experimental evaluation, and the performance is evaluated with respect to receiver operator characteristics (ROC) measure.