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Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images

Sensors (Basel, Switzerland), 2020-05, Vol.20 (11), p.3085

2020

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Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2202

2021

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Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques

Sensors (Basel, Switzerland), 2023-02, Vol.23 (5), p.2520

2023

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Manufacturing Execution System Specific Data Analysis-Use Case With a Cobot

IEEE access, 2018-01, Vol.6, p.50245-50259

2018

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Concept Mapping, an Effective Tool for Long-Term Memorization of Anatomy—A Quasi-Experimental Research Carried out among 1st Year General Medicine Students

European journal of investigation in health, psychology and education, 2020-03, Vol.10 (1), p.530-543

2020

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Integration of Real-Time Image Fusion in the Robotic-Assisted Treatment of Hepatocellular Carcinoma

Biology (Basel, Switzerland), 2020-11, Vol.9 (11), p.397

2020

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Advanced texture analysis and classification methods for the automatic diagnosis of the hepatocellular carcinoma

Applied medical informatics, 2019-09, Vol.41 (Suppl. 1), p.17-18

2019

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Computer-assisted identification of the gingival sulcus and periodontal epithelial junction on high-frequency ultrasound images

Medical ultrasonography, 2015-09, Vol.17 (3), p.273

2015

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Classification of the liver tumors Using Co-Occurrence Matrices of textural Microstructures

Journal of communication and computer, 2015-01, Vol.12 (1), p.6-12

Delia Mitrea Sergiu Nedevschi Mihail Abrudean

2015

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The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images

International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, 2016-03, Vol.5 (2), p.61-67

2016

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Periodontal evaluation using a non-invasive imaging method (ultrasonography)

Medicine and pharmacy reports, 2019-12, Vol.92 (Suppl No 3), p.S20-S32

2019

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Hepatocellular Carcinoma Recognition from Ultrasound Images Through Convolutional Neural Networks and Their Combinations

8th International Conference on Advancements of Medicine and Health Care Through Technology, 2024, Vol.102, p.3-11

2024

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The potential of ultrasonography in the evaluation of foot orthotics therapy

Medical ultrasonography, 2017-11, Vol.19 (4), p.416-422

2017

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Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images

Computational and mathematical methods in medicine, 2012-01, Vol.2012 (2012), p.1-17

2012

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HCC Recognition Within B-Mode and CEUS Images Using Traditional and Deep Learning Techniques

7th International Conference on Advancements of Medicine and Health Care Through Technology, 2021, Vol.88, p.113-120

2021

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In vitro assessment of tooth color changes due to orthodontic treatment using knowledge discovery methods

Journal of adhesion science and technology, 2015-10, Vol.29 (20), p.2256-2279

2015

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The Role of the Superior Order GLCM in the Characterization and Recognition of the Liver Tumors from Ultrasound Images

Radioengineering, 2012-04, Vol.21 (1), p.79-85

2012

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Towards Building a Computerized System for Modelling Advanced HCC Tumors, in Order to Assist Their Minimum Invasive Surgical Treatment

New Trends in Mechanism and Machine Science, 2020, Vol.89, p.219-227

2020

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Iterative Methods for Obtaining Energy-Minimizing Parametric Snakes with Applications to Medical Imaging

Computational and mathematical methods in medicine, 2012-01, Vol.2012 (2012), p.1-11

2012

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MES Specific Data Analysis. Case Study with the Baxter Robot

2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2018, p.296-301

2018

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Employing Clustering Techniques and Association Rules for Client Segmentation and Attribute Dependency Mining in the Domain of Car Insurance

World Conference of AI-Powered Innovation and Inventive Design, 2025, p.232-246

2025

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Pancreatic Tumor Recognition from CT Images through Advanced Deep Learning Techniques

2024 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), 2024, p.1-6

2024

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The Role That Web 2.0 Currently Has and Could Have in the Future in Supporting the Teaching of ICT Design for All

Technology Enhanced Learning. Quality of Teaching and Educational Reform, 2010, Vol.73, p.397-404

2010

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Hepatocellular Carcinoma Recognition from Ultrasound Images by Fusing Convolutional Neural Networks at Decision Level

2023 46th International Conference on Telecommunications and Signal Processing (TSP), 2023, p.238-243

2023

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The Role of the Feature Extraction Methods in Improving the Textural Model of the Hepatocellular Carcinoma, Based on Ultrasound Images

Digital Information Processing and Communications, 2011, p.496-509

2011

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Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images

Hepatocellular Carcinoma Automatic Diagnosis within CEUS and B-Mode Ultrasound Images Using Advanced Machine Learning Methods

Hepatocellular Carcinoma Recognition from Ultrasound Images Using Combinations of Conventional and Deep Learning Techniques

Manufacturing Execution System Specific Data Analysis-Use Case With a Cobot

Concept Mapping, an Effective Tool for Long-Term Memorization of Anatomy—A Quasi-Experimental Research Carried out among 1st Year General Medicine Students

Integration of Real-Time Image Fusion in the Robotic-Assisted Treatment of Hepatocellular Carcinoma

Advanced texture analysis and classification methods for the automatic diagnosis of the hepatocellular carcinoma

Computer-assisted identification of the gingival sulcus and periodontal epithelial junction on high-frequency ultrasound images

Classification of the liver tumors Using Co-Occurrence Matrices of textural Microstructures

The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images

Periodontal evaluation using a non-invasive imaging method (ultrasonography)

Hepatocellular Carcinoma Recognition from Ultrasound Images Through Convolutional Neural Networks and Their Combinations

The potential of ultrasonography in the evaluation of foot orthotics therapy

Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images

HCC Recognition Within B-Mode and CEUS Images Using Traditional and Deep Learning Techniques

In vitro assessment of tooth color changes due to orthodontic treatment using knowledge discovery methods

The Role of the Superior Order GLCM in the Characterization and Recognition of the Liver Tumors from Ultrasound Images

Towards Building a Computerized System for Modelling Advanced HCC Tumors, in Order to Assist Their Minimum Invasive Surgical Treatment

Iterative Methods for Obtaining Energy-Minimizing Parametric Snakes with Applications to Medical Imaging

MES Specific Data Analysis. Case Study with the Baxter Robot

Employing Clustering Techniques and Association Rules for Client Segmentation and Attribute Dependency Mining in the Domain of Car Insurance

Pancreatic Tumor Recognition from CT Images through Advanced Deep Learning Techniques

The Role That Web 2.0 Currently Has and Could Have in the Future in Supporting the Teaching of ICT Design for All

Hepatocellular Carcinoma Recognition from Ultrasound Images by Fusing Convolutional Neural Networks at Decision Level

The Role of the Feature Extraction Methods in Improving the Textural Model of the Hepatocellular Carcinoma, Based on Ultrasound Images

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