Challenges for Intelligent Data Analysis Methods in Medical Image Analysis during Surgical Interventions of Aneurysms

Abstract

Aortic aneurysms (AA) can be the primary cause of over 10,000 deaths and indirect cause for another 18,000 deaths annually in the USA as per the recent data released by the Centers for Disease Control and Prevention. Among the several factors related to high mortality, imaging methods and intervention procedures could be important. The commonly used diagnostic imaging methods of aneurysms are computed tomography (CT), magnet resonance imaging (MRI), ultrasound (US), digital subtraction angiography (DSA) and amalgamation of fluoro-D-glucose (FDG) integrated with positron emission tomography (PET) and/or CT and PET with CT or MRI. Several research findings indicate that diagnostic efficiency of different imaging methods differ. As intervention procedures depend upon diagnosis, the choice of appropriate diagnostic imaging method for a given case is very important. If the critical characteristics of the swelling are not detected due to the choice of unsuitable imaging method, interventions may not be very suitable. The American College of Radiologists (ACR) prescribed some appropriateness guidelines for diagnostic imaging. Not complying with them fully or partially may also be a mortality factor. This chapter is written with recent research findings in the field of intelligent data analysis for medical applications supported by case studies and practical examples.