Rupture prediction of abdominal aortic aneurysm using matlab, labVIEW and python in CT images

Abstract

Abdominal Aortic Aneurysm (AAA) is a substantial enlargement of the aorta that weakens the blood vessel wall leads to atherosclerotic disease. Aneurysms are dangerous because when it rupture causing hemorrhage. This leads to insufficient blood flow from the aorta to the different organs of the human body. Based on the extracted features from the AAA and the demographic data of the patient, the clinical management team will decide the optimal treatment procedure. The screening of AAA is done by ultrasound scan to know the type of the aneurysm present. Diameter with 05.05 cm or more, it should be viewed seriously. The AAA images were segmented using connected components labeling technique. Early detection of aneurysm can be repaired with proper treatment so that it does not rupture. The CT images of AAA were read and denoisedto preserve the edges using image processing software. Based on the histogram of the filtered image the AAA area was identified and threshold the image to view clearly the dilated part. The area, major axis length, minor axis length of the AAA images were calculated to understand the flow dynamics and to predict the rupture of the AAA wall using MATLAB, LabVIEW and python program.