GPU-enabled design of an adaptable pattern recognition system for discriminating squamous intraepithelial lesions of the cervix.

GPU-enabled design of an adaptable pattern recognition system for discriminating squamous intraepithelial lesions of the cervix. Biomed Tech (Berl). 2019 Nov 20;: Authors: Konstandinou C, Kostopoulos S, Glotsos D, Pappa D, Ravazoula P, Michail G, Kalatzis I, Asvestas P, Lavdas E, Cavouras D, Sakellaropoulos G Abstract The aim of the present study was to design an adaptable pattern recognition (PR) system to discriminate low- from high-grade squamous intraepithelial lesions (LSIL and HSIL, respectively) of the cervix using microscopy images of hematoxylin and eosin (H&E)-stained biopsy material from two different medical centers. Clinical material comprised H&E-stained biopsies of 66 patients diagnosed with LSIL (34 cases) or HSIL (32 cases). Regions of interest were selected from each patient's digitized microscopy images. Seventy-seven features were generated, regarding the texture, morphology and spatial distribution of nuclei. The probabilistic neural network (PNN) classifier, the exhaustive search feature selection method, the leave-one-out (LOO) and the bootstrap validation methods were used to design the PR system and to assess its precision. Optimal PR system design and evaluation were made feasible by the employment of graphics processing unit (GPU) and Compute Unified Device Architecture (CUDA) technologies. The accuracy of the PR-system was 93% and 88.6% when using the LOO and bootstrap validation methods, respectiv...
Source: Biomedizinische Technik/Biomedical Engineering - Category: Biomedical Engineering Tags: Biomed Tech (Berl) Source Type: research