D
Delia Mitrea
Researcher at Technical University of Cluj-Napoca
Publications - 50
Citations - 267
Delia Mitrea is an academic researcher from Technical University of Cluj-Napoca. The author has contributed to research in topics: Deep learning & Feature extraction. The author has an hindex of 8, co-authored 47 publications receiving 225 citations.
Papers
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Journal ArticleDOI
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images
Delia Mitrea,Paulina Mitrea,Sergiu Nedevschi,Radu Badea,Monica Lupsor,Mihai Socaciu,Adela Golea,Claudia Hagiu,Lidia Ciobanu +8 more
TL;DR: This paper considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors, and improved the computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images.
Journal Article
The Role of the Superior Order GLCM in the Characterization and Recognition of the Liver Tumors from Ultrasound Images
TL;DR: This work analyzes the role that the superior order Grey Level Cooccurrence Matrices (GLCM) and the associated parameters have in the improvement of HCC characterization and automatic diagnosis and determines the best spatial relations between the pixels that lead to the highest performances.
Journal ArticleDOI
Computer-assisted identification of the gingival sulcus and periodontal epithelial junction on high-frequency ultrasound images
Radu Chifor,Mindra Eugenia Badea,Delia Mitrea,Iulia Badea,Maria Crisan,Ioana Chifor,Ramona Avram +6 more
TL;DR: Ulasonographic examination of the periodontal tissues allows the examiner to localize the gingival epithelial attachment level and provides substantial data regarding the soft gingivals tissues.
Proceedings ArticleDOI
Texture based characterization and automatic diagnosis of the abdominal tumors from ultrasound images using third order GLCM features
TL;DR: This work analyzes the role that the third order Gray Level Cooccurrence Matrix (GLCM) has on the characterization and automatic diagnosis of the abdominal malignant tumors, and determines the best spatial relation between the pixels that leads to the highest performances.
Proceedings ArticleDOI
Ultrasonography Contribution to Hepatic Steatosis Quantification. Possibilities of Improving this Method through Computerized Analysis of Ultrasonic Image
TL;DR: The purpose is to evaluate the contribution of the ultrasonography examination to the quantification of the hepatic steatosis as well as the possibility of improving this method.