Title: A review of recent image processing techniques for liver tumour diagnosis from CT images

Authors: Farzaneh Nikroorezaei; Somayeh Saraf Esmaili

Addresses: Department of Biomedical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran ' Department of Biomedical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran

Abstract: By early detection of abnormalities using computational systems, doctors can plan an effective treatment program for the patient and increase the chance of survival. Liver cancer has a low survival rate in comparison to some other cancers and early detection significantly increases the chances of survival for people with liver cancer. This review focuses on computer-aided diagnosis (CAD) systems and describes the various image processing techniques, which have been introduced for automatic detection of liver tumours from computed tomography (CT) images. CAD systems using in liver tumour diagnosis include segmentation of liver and classify tumours whether it is cancerous or not. This paper provides a brief description of recent works that have been done in this field to improve the accuracy and speed of detection and discusses the problems and limitations of methods currently available for liver tumour diagnosis. Finally, open challenges and required researches in the field of liver tumour diagnosis are discussed.

Keywords: classification; liver tumours; computed tomography; CT; medical image processing; segmentation.

DOI: 10.1504/IJIM.2023.132322

International Journal of Image Mining, 2023 Vol.4 No.2, pp.146 - 158

Received: 25 Sep 2021
Accepted: 07 May 2022

Published online: 18 Jul 2023 *

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