Deep learning based classification for metastasis of hepatocellular carcinoma with microscopic images

Hui Meng; Yuan Gao; Kun Wang; Jie Tian

doi:10.1117/12.2512214

15 March 2019 Deep learning based classification for metastasis of hepatocellular carcinoma with microscopic images

Hui Meng, Yuan Gao, Kun Wang, Jie Tian

Proceedings Volume 10949, Medical Imaging 2019: Image Processing; 109492L (2019) https://doi.org/10.1117/12.2512214
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. The high probability of metastasis makes its prognosis very poor even after potentially curative treatment. Detecting high metastatic HCC will allow for the development of effective approaches to reduce HCC mortality. The mechanism of HCC metastasis has been studied using gene profiling analysis, which indicated that HCC with different metastatic capability was differentiable. However, it is time consuming and complex to analyze gene expression level with conventional method. To distinguish HCC with different metastatic capabilities, we proposed a deep learning based method with microscopic images in animal models. In this study, we adopted convolutional neural networks (CNN) to learn the deep features of microscopic images for classifying each image into low metastatic HCC or high metastatic HCC. We evaluated our proposed classification method on the dataset containing 1920 white-light microscopic images of frozen sections from three tumor-bearing mice injected with HCC-LM3 (high metastasis) tumor cells and another three tumor-bearing mice injected with SMMC-7721(low metastasis) tumor cells. Experimental results show that our method achieved an average accuracy of 0.85. The preliminary study demonstrated that our deep learning method has the potential to be applied to microscopic images for metastasis of HCC classification in animal models.

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Hui Meng, Yuan Gao, Kun Wang, and Jie Tian "Deep learning based classification for metastasis of hepatocellular carcinoma with microscopic images", Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109492L (15 March 2019); https://doi.org/10.1117/12.2512214

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KEYWORDS

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Image classification

Animal model studies

Convolutional neural networks

Visualization

Cancer

Image analysis

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