Diagnostic discrimination of biological tissue samples using artificial intelligence

Research theses
Abstract

Within the framework of this practicum within the Biomedical Engineering research group at the University of Cantabria, students will be able to be integrated into research activities developed by the group, particularly those related to diagnostic discrimination systems for biological tissues using artificial intelligence techniques. Current clinical diagnosis presents discriminative difficulties, especially with low-contrast biological tissues. By using electromagnetic radiation, it is possible to obtain relevant diagnostic information, even in low-contrast biological tissues. Parameters based on intrinsic information such as intensity, spectral, polarimetric, or phase give rise to novel diagnostic systems when combined with artificial intelligence elements.

Keywords
Biomedical Engineering
diagnostic discrimination
label-free diagnosis
artificial intelligence
biomedical media
ERC sector(s)
PE Physical Sciences and Engineering
Thesis supervisor
Name supervisor
Félix Fanjul Vélez
E-mail
eunice@unican.es
Department/Faculty/School/Institute/Area/Division NAME
Department of Electronic Technology, Systems and Automation Engineering (TEISA)
Name of the host University
University of Cantabria (UC)
EUNICE partner e-mail of destination Research
area.eunice@unican.es
Country
Spain
Student profile
Thesis level
Master
Minimal language knowledge requisite
English B2
Additional info
Length of the research internship
3 months
Financial support available (other than E+)
No
Research interests for cooperation opportunities
Electromagnetic, electropysiological and acoustic techniques for biomedical media diagnosis, structural and molecular characterization, treatment and surgery, including endoscopes