Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images
The emergence of deep-learning methods in different computer vision tasks has proved to offer increased detection, recognition or segmentation accuracy when large annotated image datasets are available. In the case of medical image processing and computer-aided diagnosis within ultrasound images, wh...
Main Authors: | Raluca Brehar, Delia-Alexandrina Mitrea, Flaviu Vancea, Tiberiu Marita, Sergiu Nedevschi, Monica Lupsor-Platon, Magda Rotaru, Radu Ioan Badea |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/11/3085 |
Similar Items
-
Advanced texture analysis and classification methods for the automatic diagnosis of the Hepatocellular Carcinoma
by: Delia MITREA, et al.
Published: (2019-09-01) -
Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods
by: Delia Mitrea, et al.
Published: (2021-03-01) -
The Role of the Superior Order GLCM in the Characterization and Recognition of the Liver Tumors from Ultrasound Images
by: D. Mitrea, et al.
Published: (2012-04-01) -
Integration of Real-Time Image Fusion in the Robotic-Assisted Treatment of Hepatocellular Carcinoma
by: Corina Radu, et al.
Published: (2020-11-01) -
Hepatocellular Carcinoma. Part 2: Clinical Presentation and Diagnosis
by: Lior Charach, et al.
Published: (2017-06-01)