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Current Medical Imaging

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ISSN (Online): 1875-6603

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Review Article

Chest CT Image based Lung Disease Classification – A Review

Author(s): Shri Ramtej Kondamuri*, Venkata Sainath Gupta Thadikemalla, Gunnam Suryanarayana, Chandran Karthik, Vanga Siva Reddy, V. Bhuvana Sahithi, Y. Anitha, V. Yogitha and P. Reshma Valli

Volume 20, 2024

Published on: 16 October, 2023

Article ID: e15734056248176 Pages: 14

DOI: 10.2174/0115734056248176230923143105

open_access

Abstract

Computed tomography (CT) scans are widely used to diagnose lung conditions due to their ability to provide a detailed overview of the body's respiratory system. Despite its popularity, visual examination of CT scan images can lead to misinterpretations that impede a timely diagnosis. Utilizing technology to evaluate images for disease detection is also a challenge. As a result, there is a significant demand for more advanced systems that can accurately classify lung diseases from CT scan images. In this work, we provide an extensive analysis of different approaches and their performances that can help young researchers to build more advanced systems. First, we briefly introduce diagnosis and treatment procedures for various lung diseases. Then, a brief description of existing methods used for the classification of lung diseases is presented. Later, an overview of the general procedures for lung disease classification using machine learning (ML) is provided. Furthermore, an overview of recent progress in ML-based classification of lung diseases is provided. Finally, existing challenges in ML techniques are presented. It is concluded that deep learning techniques have revolutionized the early identification of lung disorders. We expect that this work will equip medical professionals with the awareness they require in order to recognize and classify certain medical disorders.

Keywords: Computed tomography, Lung cancer, Pneumonia, Pulmonary embolism, Machine learning, Convolutional neural networks.

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