Teaching image processing and artificial neural networks in engineering - A case study in medicine

Abstract

This work presents a case study in the field of medicine employing digital image processing and artificial intelligence techniques based on artificial neural networks. The application consists on the development of a software for the treatment of images captured in vascular ultrasound exams with color Doppler in order to diagnose carotid percentage occlusion (carotid stenosis). The developed application can be used as a tool for engineering education, allowing the use and evaluation of several image processing techniques in engineering, such as character recognition, color identification, filtering and contour detection, among other techniques. Additionally, it allows the integration of neural network concepts for data processing. © 2022 IEEE.