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.
|Журнал||IEEE Journal of Selected Topics in Quantum Electronics|
|Состояние||Опубликовано - 1 сен 2021|
Предметные области OECD FOS+WOS
- 2.02 ЭЛЕКТРОТЕХНИКА, ЭЛЕКТРОННАЯ ТЕХНИКА, ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ
- 1.03 ФИЗИЧЕСКИЕ НАУКИ И АСТРОНОМИЯ