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

Autor: Delia Alexandrina Mitrea, Sergiu Nedevschi, Mihail Abrudean, Radu Chifor, Radu Badea

Publikováno v: International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, Vol 5, Iss 2, Pp 61-67 (2016)

The non-invasive diagnosis, based on ultrasound images, is a challenge in nowadays research. We develop computerized, texture-based methods, for automatic and computer assisted diagnosis, using the information obtained from ultrasound images. In this

Externí odkaz: https://doaj.org/article/95b64504350d4124950f0d72620da453

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

Autor: Delia-Alexandrina Mitrea, Ioana Chifor, Alexandru Florin Badea, Mindra Eugenia Badea, Maria Crisan, Radu Chifor

Publikováno v: Medicine and Pharmacy Reports

The periodontal disease and gingival bleeding are highly prevalent in the adult population worldwide. The World Health Organization (WHO) data shows that 90–100% of the 34-year-old adults present gingival inflammation. Therefore, an investigation m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e729843e79ff173aadfbbf89c4bc7fb
http://europepmc.org/articles/PMC6978923

The Role of Convolutional Neural Networks in the Automatic Recognition of the Hepatocellular Carcinoma, Based on Ultrasound Images

Autor: Radu Badea, Monica Lupsor Platon, Sergiu Nedevschi, Paulina Mitrea, Raluca Brehar, Delia-Alexandrina Mitrea

Publikováno v: 6th International Conference on Advancements of Medicine and Health Care through Technology; 17–20 October 2018, Cluj-Napoca, Romania ISBN: 9789811362064

Hepatocellular carcinoma (HCC) represents the most frequent form of liver cancer. It evolves from cirrhosis, as the result of a restructuring phase at the end of which dysplastic nodules appear. HCC is the main cause of death in people affected by ci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6c9a592d0bf9ffe812c5389e43e657ea
https://doi.org/10.1007/978-981-13-6207-1_27

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

Autor: Raluca Brehar, Delia-Alexandrina Mitrea, Flaviu Vancea, Tiberiu Marita, Sergiu Nedevschi, Monica Lupsor-Platon, Magda Rotaru, Radu Ioan Badea

Publikováno v: Sensors, Vol 20, Iss 11, p 3085 (2020)

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 com

Externí odkaz: https://doaj.org/article/4a054dbdb90b41aaaba1fe1153c0c79b