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Automated Measurement of Abdominal A...

Hashempour, Vahideh.

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Automated Measurement of Abdominal Aorta Diameter in Abdominal CT Scan Images Using AI-Driven Image Processing.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Automated Measurement of Abdominal Aorta Diameter in Abdominal CT Scan Images Using AI-Driven Image Processing./
Author:	Hashempour, Vahideh.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2024,
Description:	40 p.
Notes:	Source: Masters Abstracts International, Volume: 86-03.
Contained By:	Masters Abstracts International86-03.
Subject:	Computer engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31490267
ISBN:	9798384079507

Automated Measurement of Abdominal Aorta Diameter in Abdominal CT Scan Images Using AI-Driven Image Processing.
Hashempour, Vahideh.

Automated Measurement of Abdominal Aorta Diameter in Abdominal CT Scan Images Using AI-Driven Image Processing. - Ann Arbor : ProQuest Dissertations & Theses, 2024 - 40 p.

Source: Masters Abstracts International, Volume: 86-03.

Thesis (M.S.)--The University of Texas at San Antonio, 2024.

Measuring the diameter of the abdominal aorta accurately is essential for the early detection and management of vascular conditions, including aneurysms. Traditional manual measurement methods using abdominal CT scan images are prone to variability and inefficiency. This thesis investigates the utilization of artificial intelligence (AI) techniques in image processing to automate and enhance the measurement of the abdominal aorta diameter. By leveraging deep learning models and convolutional neural networks, the study develops an AI-based system capable of identifying and measuring the aorta with high precision from CT scans. Findings indicate that the AI approach not only expedites the measurement process but also maintains high accuracy, suggesting a significant potential for clinical application. This work demonstrates the transformative impact of AI on medical imaging and its role in advancing diagnostic accuracy and efficiency.

ISBN: 9798384079507Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

Abdominal aorta

Automated Measurement of Abdominal Aorta Diameter in Abdominal CT Scan Images Using AI-Driven Image Processing.
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300 $a 40 p.
500 $a Source: Masters Abstracts International, Volume: 86-03.
500 $a Advisor: Alamaniotis, Miltos;Miserlis, Dimitrios.
502 $a Thesis (M.S.)--The University of Texas at San Antonio, 2024.
520 $a Measuring the diameter of the abdominal aorta accurately is essential for the early detection and management of vascular conditions, including aneurysms. Traditional manual measurement methods using abdominal CT scan images are prone to variability and inefficiency. This thesis investigates the utilization of artificial intelligence (AI) techniques in image processing to automate and enhance the measurement of the abdominal aorta diameter. By leveraging deep learning models and convolutional neural networks, the study develops an AI-based system capable of identifying and measuring the aorta with high precision from CT scans. Findings indicate that the AI approach not only expedites the measurement process but also maintains high accuracy, suggesting a significant potential for clinical application. This work demonstrates the transformative impact of AI on medical imaging and its role in advancing diagnostic accuracy and efficiency.
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650 4 $a Medical imaging. $3 3172799
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653 $a Image processing
653 $a Deep learning models
653 $a Computed tomography
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690 $a 0574
690 $a 0800
710 2 $a The University of Texas at San Antonio. $b Electrical & Computer Engineering. $3 1018585
773 0 $t Masters Abstracts International $g 86-03.
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793 $a English
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