Deep Learning-Based Hepatocellular Carcinoma Histopathology Image Classification: Accuracy Versus Training Dataset Size
Globally, liver cancer causes more than 700,000 deaths each year and is the second-leading cause of death from cancer. Hepatocellular carcinoma (HCC) is the most common type of liver cancer in adults and accounts for most deaths in cirrhosis patients. Patients with early-stage liver cancer can be tr...
Main Authors: | Yu-Shiang Lin, Pei-Hsin Huang, Yung-Yaw Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9359762/ |
Similar Items
-
Deep learning‐based classification and mutation prediction from histopathological images of hepatocellular carcinoma
by: Haotian Liao, et al.
Published: (2020-06-01) -
Prognostic analysis of histopathological images using pre-trained convolutional neural networks: application to hepatocellular carcinoma
by: Liangqun Lu, et al.
Published: (2020-03-01) -
Immunohistochemical, histopathological study and chemoprotective effect of Solanum nigrum in N-nitrosodiethylamine-induced hepatocellular carcinoma in Wistar rats
by: G. M. Akshatha, et al.
Published: (2018-04-01) -
Classification of Diabetic Rat Histopathology Images Using Convolutional Neural Networks
by: Ahmet Haşim Yurttakal, et al.
Published: (2020-11-01) -
Qualitative Histopathological Classification of Primary Bone Tumors Using Deep Learning: A Pilot Study
by: Yuzhang Tao, et al.
Published: (2021-10-01)