Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

M. A. Alam; M. B. Shakir; M. A. Hossain; M. I. Pavel; K. M. A. Shams; F. R. Akib

doi:10.1117/12.2293965

6 March 2018 Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

M. A. Alam, M. B. Shakir, M. A. Hossain, M. I. Pavel, K. M. A. Shams, F. R. Akib

Author Affiliations +

Proceedings Volume 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications; 105791J (2018) https://doi.org/10.1117/12.2293965
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

This proposed method aims towards a full automation of the detection of coronary artery blockage through some image processing techniques so that the system does not have to rely on human's inspection. The goal of the research is to implement the proposed image processing techniques so the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the preprocessing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. In order to get more insights of the subject of these examinations, this research has proposed the use of an algorithm to create a 3-D model.

Citation Download Citation

M. A. Alam, M. B. Shakir, M. A. Hossain, M. I. Pavel, K. M. A. Shams, and F. R. Akib "Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique", Proc. SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105791J (6 March 2018); https://doi.org/10.1117/12.2293965

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available