BLAHUTA, Jiří, Tomáš SOUKUP a Jiří MARTINŮ. An expert system based on using artificial neural network and region-based image processing to recognition substantia nigra and atherosclerotic plaques in b-images: A prospective study. Online. In ROJAS, Ignacio; JOYA, Gonzalo; CATALA, Andreu. Lecture Notes in Computer Science. Volume 10305. Cham: Springer Verlag, 2017, s. 236-245. ISBN 978-3-319-59152-0. Dostupné z: https://dx.doi.org/10.1007/978-3-319-59153-7_21.
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Základní údaje
Originální název An expert system based on using artificial neural network and region-based image processing to recognition substantia nigra and atherosclerotic plaques in b-images: A prospective study
Autoři BLAHUTA, Jiří (203 Česká republika, garant, domácí), Tomáš SOUKUP (203 Česká republika) a Jiří MARTINŮ (203 Česká republika, domácí).
Vydání Volume 10305. Cham, Lecture Notes in Computer Science, od s. 236-245, 10 s. 2017.
Nakladatel Springer Verlag
Další údaje
Originální jazyk angličtina
Typ výsledku Stať ve sborníku
Obor 10201 Computer sciences, information science, bioinformatics
Stát vydavatele Německo
Utajení není předmětem státního či obchodního tajemství
Forma vydání elektronická verze "online"
WWW URL
Kód RIV RIV/47813059:19240/17:A0000123
Organizace Filozoficko-přírodovědecká fakulta – Slezská univerzita v Opavě – Repozitář
ISBN 978-3-319-59152-0
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-319-59153-7_21
Klíčová slova anglicky B-images; B-MODE; Neural networks ultrasound; Parkinson’s disease; Stroke ultrasound; Substantia nigra; Ultrasound
Štítky ÚI
Příznaky Mezinárodní význam, Recenzováno
Návaznosti LQ1602, projekt VaV.
Změnil Změnil: Mgr. Kamil Matula, učo 1145. Změněno: 20. 3. 2018 13:31.
Anotace
The presented paper is focused on ways of digital image analysis of ultrasound B-images based on echogenicity investigation in determined Region of Interest (ROI). An expert system has been developed in the course of the research. The goal of the paper is to demonstrate how to interconnect automatic finding of the position of the substantia nigra using Artificial Neural Network (ANN) with supervised learning and ROI-based image analysis. For substantia nigra is able to detect the position using ANN from B-image in transverse thalamic plane. From this is computed echogenicity index grade inside the ROI as parkinsonism feature. The methodology is well applicable for a set of images with the same resolution. The results have shown practical application of ANN learning in this case. The second part of the paper is focused on detection of atherosclerotic plaques. An experimental prospective study shown the using ANN can be highly time-consuming problem due to complexity of B-images. The plaques have no standardized shape and size in comparison with SN. To objective appraisal of using ANN to automatic finding atherosclerotic plaque in B-image we need a large set of images of normal and pathological state. Although it is very important using ANN, automatic detection in highly time-consuming problem for ANN training.
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