The Discrete Analysis of the Tissue Biopsy Images with Metamaterial Formalization: Identifying Tumor Locus

Tatjana Gric, Sergei Sokolovski, Alexander Alekseev, Andrian Mamoshin, Andrey Dunaev, Edik Rafailov

Результат исследования: Научные публикации в периодических изданияхстатьярецензирование

Аннотация

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.

Язык оригиналаанглийский
Номер статьи9363516
ЖурналIEEE Journal of Selected Topics in Quantum Electronics
Том27
Номер выпуска5
DOI
СостояниеОпубликовано - 1 сен 2021

Предметные области OECD FOS+WOS

  • 2.02 ЭЛЕКТРОТЕХНИКА, ЭЛЕКТРОННАЯ ТЕХНИКА, ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ
  • 1.03 ФИЗИЧЕСКИЕ НАУКИ И АСТРОНОМИЯ

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