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Open Access

Study of Texture Segmentation and Classification for Grading Small Hepatocellular Carcinoma Based on CT Images

School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China.
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.
Department of Radiology of Peking Union Medical College Hospital, Beijing 100032, China.
Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.
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Abstract

To grade Small Hepatocellular CarCinoma (SHCC) using texture analysis of CT images, we retrospectively analysed 68 cases of Grade II (medium-differentiation) and 37 cases of Grades III and IV (high-differentiation). The grading scheme follows 4 stages: (1) training a Super Resolution Generative Adversarial Network (SRGAN) migration learning model on the Lung Nodule Analysis 2016 Dataset, and employing this model to reconstruct Super Resolution Images of the SHCC Dataset (SR-SHCC) images; (2) designing a texture clustering method based on Gray-Level Co-occurrence Matrix (GLCM) to segment tumour regions, which are Regions Of Interest (ROIs), from the original and SR-SHCC images, respectively; (3) extracting texture features on the ROIs; (4) performing statistical analysis and classifications. The segmentation achieved accuracies of 0.9049 and 0.8590 in the original SHCC images and the SR-SHCC images, respectively. The classification achived an accuracy of 0.838 and an Area Under the ROC Curve (AUC) of 0.84. The grading scheme can effectively reduce poor impacts on the texture analysis of SHCC ROIs. It may play a guiding role for physicians in early diagnoses of medium-differentiation and high-differentiation in SHCC.

Keywords

grading of Small Hepatocellular CarCinoma (SHCC)Gray-Level Co-occurrence Matrix (GLCM)texture clusteringsuper-resolution reconstruction

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Tsinghua Science and Technology
Volume 26 Issue 2,
April 2021
Pages 199-207
DOI: 10.26599/TST.2019.9010058
Cite this article:
Hui B, Liu Y, Qiu J, et al. Study of Texture Segmentation and Classification for Grading Small Hepatocellular Carcinoma Based on CT Images. Tsinghua Science and Technology, 2021, 26(2): 199-207. https://doi.org/10.26599/TST.2019.9010058

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Received: 29 September 2019
Revised: 03 December 2019
Accepted: 02 January 2020
Published: 24 July 2020
© The author(s) 2021.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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