dc.contributor.author | Gric, Tatjana | |
dc.contributor.author | Sokolovski, Sergei G. | |
dc.contributor.author | Alekseev, Alexander G. | |
dc.contributor.author | Mamoshin, Andrian | |
dc.contributor.author | Dunaev, Andrey | |
dc.contributor.author | Rafailov, Edik U. | |
dc.date.accessioned | 2023-09-18T20:38:19Z | |
dc.date.available | 2023-09-18T20:38:19Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 1077-260X | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/151532 | |
dc.description.abstract | Herein, we develop an enhanced and automated methodology for detection of the tumour cells in fixed biopsy samples. Metamaterial formalism (MMF) approach allowing recognition of tumour areas in tissue samples is enhanced by providing an advanced technique to digitize mouse biopsy images. Thus, a colour-based segmentation technique based on the K-means clustering method is used allowing for a precise segmentation of the cells composing the biological tissue sample. Errors occurring at the tissue digitization steps are detected by applying MMF. Doing so, we end up with the robust, fully automated approach with no needs of the human intervention, ready for the clinical applications. The proposed methodology consists of three major steps, i. e. digitization of the biopsy image, analysis of the biopsy image, modelling of the disordered metamaterial. It is worthwhile mentioning, that the technique under consideration allows for the cancer stage detection. Moreover, early stage cancer diagnosis is possible by applying MMF. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-8 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | IEEE Xplore | |
dc.relation.isreferencedby | PubMed | |
dc.relation.isreferencedby | Scopus | |
dc.rights | Prieinamas tik institucijos(-ų) intranete | |
dc.source.uri | https://ieeexplore.ieee.org/document/9363516 | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:85682522/datastreams/MAIN/content | |
dc.title | The discrete analysis of the tissue biopsy images with metamaterial formalization: identifying tumour locus | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 43 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas Valstybinis mokslinių tyrimų institutas Fizinių ir technologijos mokslų centras Aston University | |
dc.contributor.institution | Aston University Novosibirsk State University | |
dc.contributor.institution | Orel State University Clinical Multidisciplinary Center for Medical Care for Mothers and Children named after Z.I. Krugloy | |
dc.contributor.institution | Orel State University Orel Region Clinical Hospital | |
dc.contributor.institution | Orel State University | |
dc.contributor.institution | Aston University Peter the Great St. Petersburg Polytechnic University | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.researchfield | N 002 - Fizika / Physics | |
dc.subject.studydirection | F05 - Biotechnologijos / Biotechnology | |
dc.subject.vgtuprioritizedfields | FM0101 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai / Mathematical models of physical, technological and economic processes | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | biopsy | |
dc.subject.en | metamaterial | |
dc.subject.en | tumour | |
dcterms.sourcetitle | IEEE journal of selected topics in quantum electronics | |
dc.description.issue | iss. 5 | |
dc.description.volume | vol. 27 | |
dc.publisher.name | IEEE | |
dc.publisher.city | Piscataway, NJ | |
dc.identifier.doi | 10.1109/JSTQE.2021.3061960 | |
dc.identifier.elaba | 85682522 | |