Radu Badea
Orcid: 0000-0002-5330-090X
According to our database1,
Radu Badea
authored at least 35 papers
between 2010 and 2024.
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Bibliography
2024
Pancreatic Tumor Recognition from CT Images through Advanced Deep Learning Techniques.
Proceedings of the IEEE International Conference on Automation, 2024
2023
Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques.
Sensors, March, 2023
Hepatocellular Carcinoma Recognition from Ultrasound Images by Fusing Convolutional Neural Networks at Decision Level.
Proceedings of the 46th International Conference on Telecommunications and Signal Processing, 2023
Liver Tumor Segmentation From Computed Tomography Images Through Convolutional Neural Networks.
Proceedings of the 9th International Conference on Systems and Informatics, 2023
2021
Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods.
Sensors, 2021
2020
Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images.
Sensors, 2020
Adversarial Graph Learning and Deep Learning Techniques for improving diagnosis within CT and Ultrasound images.
Proceedings of the 16th IEEE International Conference on Intelligent Computer Communication and Processing, 2020
2019
Hepatocellular Carcinoma Segmentation within Ultrasound Images using Convolutional Neural Networks.
Proceedings of the 15th IEEE International Conference on Intelligent Computer Communication and Processing, 2019
Hepatocellular Carcinoma Recognition in Ultrasound Images Using Textural Descriptors and Classical Machine Learning.
Proceedings of the 15th IEEE International Conference on Intelligent Computer Communication and Processing, 2019
HCC Recognition Within Ultrasound Images Employing Advanced Textural Features with Deep Learning Techniques.
Proceedings of the 12th International Congress on Image and Signal Processing, 2019
2018
Automatic Recognition of the Hepatocellular Carcinoma from Ultrasound Images using Complex Textural Microstructure Co-Occurrence Matrices (CTMCM).
Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, 2018
2017
Cognitive Radio Network and Network Service Chaining toward 5G: Challenges and Requirements.
IEEE Commun. Mag., 2017
The role of the cooccurrence matrix based on complex extended microstructures in discovering the cirrhosis severity grades within US images.
Proceedings of the 10th International Congress on Image and Signal Processing, 2017
2016
The Role of the Complex Extended Textural Microstructure Co-occurrence Matrix in the Unsupervised Detection of the HCC Evolution Phases, based on Ultrasound Images.
Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods, 2016
Advanced Texture Analysis Techniques for Building Textural Models, with Applications in the Study of the Pathology Evolution Stages, based on Ultrasound Images.
Proceedings of the European Project Space on Intelligent Technologies, 2016
2015
Colorectal cancer recognition from ultrasound images, using complex textural microstructure cooccurrence matrices, based on Laws' features.
Proceedings of the 38th International Conference on Telecommunications and Signal Processing, 2015
2014
Classification of the Liver Tumors using Multiresolution, Superior Order EOCM Textural Features.
Proceedings of the ICPRAM 2014, 2014
Proceedings of the 10th International Conference on Communications, 2014
Diseased tissue area detection and delimitation, by fusion between finite difference methods and textural analysis.
Proceedings of the IEEE International Conference on Automation, 2014
2013
Comput. Math. Methods Medicine, 2013
Discovering the cirrhosis grades from ultrasound images by using textural features and clustering methods.
Proceedings of the 36th International Conference on Telecommunications and Signal Processing, 2013
2012
Intelligent decision-making for liver fibrosis stadialization based on tandem feature selection and evolutionary-driven neural network.
Expert Syst. Appl., 2012
Influence of Expert-Dependent Variability over the Performance of Noninvasive Fibrosis Assessment in Patients with Chronic Hepatitis C by Means of Texture Analysis.
Comput. Math. Methods Medicine, 2012
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images.
Comput. Math. Methods Medicine, 2012
Iterative Methods for Obtaining Energy-Minimizing Parametric Snakes with Applications to Medical Imaging.
Comput. Math. Methods Medicine, 2012
Multicriteria Optimization Model for the Study of the Efficacy of Skin Antiaging Therapy.
Comput. Math. Methods Medicine, 2012
Comput. Math. Methods Medicine, 2012
The Role of the Multiresolution Textural Features in Improving the Characterization and Recognition of the Liver Tumors, Based on Ultrasound Images.
Proceedings of the 14th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2012
2011
Feature selection for a cooperative coevolutionary classifier in liver fibrosis diagnosis.
Comput. Biol. Medicine, 2011
Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C.
Artif. Intell. Medicine, 2011
The role of the superior order GLCM in improving the automatic diagnosis of the hepatocellular carcinoma based on ultrasound images.
Proceedings of the 34th International Conference on Telecommunications and Signal Processing (TSP 2011), 2011
The Role of the Feature Extraction Methods in Improving the Textural Model of the Hepatocellular Carcinoma, Based on Ultrasound Images.
Proceedings of the Digital Information Processing and Communications, 2011
Texture analysis as a noninvasive tool for fibrosis assessment in chronic hepatitis C. influence of expert dependent variability over the performance of texture analysis.
Proceedings of the IEEE International Conference on Intelligent Computer Communication and Processing, 2011
The role of the superior order GLCM and of the generalized cooccurrence matrices in the characterization and automatic diagnosis of the hepatocellular carcinoma, based on ultrasound images.
Proceedings of the IEEE International Conference on Intelligent Computer Communication and Processing, 2011
2010
Proceedings of the Computational Science and Its Applications, 2010