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Angioinspect: Image processing-based coronary angiography assistant

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2023
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Abstract (EN)

Patients with coronary artery blockage or stenosis require the placement of a stent. Determining the appropriate stent length often relies on the physician's experience and intuition. This circumstance can lead to the placement of stents that are either excessively long or short. The objective of this project is to develop software that calculates the stent length, which can be easily utilized by healthcare professionals. This way, errors during stent placement will be minimized, contributing to an improved quality of life for patients. The project facilitates access to the software for healthcare professionals in any setting with internet connectivity, utilizing image processing algorithms that analyze coronary arteries. The process begins with the healthcare professional enclosing a region with a clear catheter in a rectangle to accurately calculate the stent length. They must select the blocked region using Bezier curves. Subsequently, the software recommends the appropriate stent length by considering the catheter's diameter. Our image processing algorithms enable users to effectively outline the catheter diameter and the blocked coronary artery. Identification of pixels representing the blocked area within the image is enabled. These pixel data are utilized during image processing to calculate the correct stent length. In conclusion, the developed web-based software provides a reliable and user-friendly environment for calculating stent length based on visual assessments by physicians. The project has the potential to minimize errors in stent selection, thus contributing to the treatment outcomes of patients with coronary artery blockage or stenosis.

Author

Mustafa Alpkan Çiçek

How to Cite

Mustafa Alpkan Çiçek (Master Thesis). Angioinspect: Image processing-based coronary angiography assistant, 2023, Bahçeşehir University.

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