Research Progress of Deep Learning in Diagnosis, Treatment and Prognosis Assessment of Hepatocellular Carcinoma

Mianlei Lin; Qian Wu; Caitao Zhao; Yingning Wu

doi:10.54097/18qm3f54

Authors

Mianlei Lin
Qian Wu
Caitao Zhao
Yingning Wu

DOI:

https://doi.org/10.54097/18qm3f54

Keywords:

Hepatocellular Carcinoma, Deep Learning, Convolutional Beutral Network, Microvascular Invasion, Transhepatic Arterial Chem Otherapy and Embolization

Abstract

Hepatic carcinoma (HCC) is a common malignant tumor in the abdominal system in China. Due to its high degree of malignancy, poor prognosis and easy recurrence, there are many therapeutic programs available, but the results are not satisfactory. The use of deep learning (DL) for diagnosis, treatment and prognosis assessment of HCC patients has become a hot topic at present. Therefore, this paper reviews the application of DL in early diagnosis, microvascular infiltration, pathological grading and postoperative evaluation of HCC.

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