Automatic Detection of Liver Cancer Using Hybrid Pre-Trained Models
Liver cancer is a life-threatening illness and one of the fastest-growing cancer types in the world. Consequently, the early detection of liver cancer leads to lower mortality rates. This work aims to build a model that will help clinicians determine the type of tumor when it occurs within the liver...
Main Authors: | Esam Othman, Muhammad Mahmoud, Habib Dhahri, Hatem Abdulkader, Awais Mahmood, Mina Ibrahim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-07-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/22/14/5429 |
Similar Items
-
Classification Efficiency of Pre-Trained Deep CNN Models on Camera Trap Images
by: Adam Stančić, et al.
Published: (2022-01-01) -
Data Balancing Based on Pre-Training Strategy for Liver Segmentation from CT Scans
by: Yong Zhang, et al.
Published: (2019-05-01) -
Classification of defects in wooden structures using pre-trained models of convolutional neural network
by: Rana Ehtisham, et al.
Published: (2023-12-01) -
Automatic liver and tumour segmentation from CT images using Deep learning algorithm
by: R.V. Manjunath, et al.
Published: (2022-03-01) -
Fine Tuning CNN Pre-trained Model Based on Thermal Imaging for Obesity Early Detection
by: Hendrik Leo, et al.
Published: (2022-04-01)