Enhancing X-ray Diagnosis through AI: Lung Disease Detection

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Date

2023

Journal Title

Journal ISSN

Volume Title

Publisher

Lviv Polytechnic National University

Abstract

Master’s degree work of the student of the group CSAI-22 Dariia Khoroshchuk. The topic is “Enhancing X-ray Diagnosis through AI: Lung Disease Detection”. The work aims to obtain a master’s degree in 122 “Computer Science”. The object of the research is the development and optimization of the pneumothorax detection system, considering the bias of the models towards the presence of chest tubes. The subject of the research involves methods for enhancing the processing of chest X-ray scans to achieve precise and rapid pneumothorax detection. The goal of the research is achieved by improving existing methods for detecting pneumothorax in X-ray scans without the presence of chest tubes. These cases are regarded as potentially positive and demand careful consideration by healthcare professionals. Additionally, the research encompasses methods to identify chest tubes on X-rays, allowing the categorization of such scans as pneumothorax negative. The presence of chest tubes on X-ray scans indicates that the patient has already received the necessary medical assistance. As a result of the master’s qualification work, a system was developed to determine the presence of a chest tube, followed by the identification of pneumothorax in cases where a tube is absent. The total volume of work: 72 pages, 34 figures, 39 references.

Description

Keywords

pneumothorax, chest X-ray, deep learning, classification, chest tubes

Citation

Khoroshchuk D. Enhancing X-ray Diagnosis through AI: Lung Disease Detection : explanatory note to the bachelor's level qualification thesis : 122 «Computer Science» / Dariia Khoroshchuk ; Lviv Polytechnic National University. – Lviv, 2023. – 72 p.