Open AccessProbabilistic Neural Network and Genetic Algorithm for Abdominal Aorta Aneurysm Identification
Author(s) -
S. Anandh,
R. Vasuki,
Raid Al Baradie
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.c9123.019320
Subject(s) - computer science , classifier (uml) , probabilistic logic , segmentation , artificial neural network , artificial intelligence , probabilistic neural network , identification (biology) , genetic algorithm , abdominal aortic aneurysm , pattern recognition (psychology) , abdominal aorta , naive bayes classifier , algorithm , machine learning , aneurysm , aorta , medicine , radiology , botany , biology , time delay neural network , support vector machine
An abdominal aorta aneurysm (AAA) can cause severe threat if it burst. Doctors can detect the presence of AAA by using abdominal ultrasound. As the treatment depends on the location and size, accuracy plays a significant role. To prevent devastating clinical outcome in this proposed work, new approaches and algorithms were used for generating the infallible result. After processing the AAA image by using notch filter, exudate based segmentation is performed and the selected features gets classified by using probabilistic neural network classifier. By using PNN classifier, accuracy and sensitivity gets enhanced in this work. The achieved accuracy is 98% and sensitivity 97.5%. While analogizing the proposed work with other existing work. It’s very facile to perform and expected target gets achieved