Abstract

Investigation of membrane fluidity by two photon fluorescence microscopy opens up a new and important area of translational research, being a useful and sensitive method for disease monitoring and treatment. In this paper we investigate if biomembranes in human red blood cells (RBC) and peripheral mononuclear cells (PMC) could be used as markers for type 1 diabetes mellitus (T1DM) diagnosis, leading to the development of a method for monitoring T1DM progression that nowadays is lacking, as clinical exams cannot pursue this task with enough reliability. To this aim, we present a set of features computed from PMC and RBC images that are given to a multi-experts system leveraging on multi-spectral information for positive/negative classifications. The experiments are carried out on a dataset of 800 blood cell images belonging to 18 subjects adopting the leave-one-person-out approach.
Lingua originaleEnglish
pagine (da-a)197-202
Numero di pagine6
RivistaPROCEEDINGS - IEEE SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS
Volume2016-
DOI
Stato di pubblicazionePubblicato - 2016
Evento29th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2016 - Trinity College Health Sciences Building at St. James's Hospital, irl
Durata: 20 giu 201623 giu 2016

Keywords

  • Computer Science Applications1707 Computer Vision and Pattern Recognition
  • Feature extraction
  • Image processing
  • Machine learning
  • Radiology, Nuclear Medicine and Imaging
  • Two photon microscopy
  • Type 1 Diabetes

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