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@inproceedings{28543, author = {BLAHUTA, Jiří and SOUKUP, Tomáš and MARTINŮ, Jiří}, address = {Cham}, booktitle = {Lecture Notes in Computer Science}, doi = {http://dx.doi.org/10.1007/978-3-319-59153-7_21}, edition = {Volume 10305}, editor = {ROJAS, Ignacio; JOYA, Gonzalo; CATALA, Andreu}, keywords = {B-images; B-MODE; Neural networks ultrasound; Parkinson’s disease; Stroke ultrasound; Substantia nigra; Ultrasound}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Cham}, isbn = {978-3-319-59152-0}, pages = {236-245}, publisher = {Springer Verlag}, title = {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}, url = {https://link.springer.com/chapter/10.1007%2F978-3-319-59153-7_21}, year = {2017} }
TY - JOUR ID - 28543 AU - BLAHUTA, Jiří - SOUKUP, Tomáš - MARTINŮ, Jiří PY - 2017 TI - 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 PB - Springer Verlag CY - Cham SN - 9783319591520 KW - B-images KW - B-MODE KW - Neural networks ultrasound KW - Parkinson’s disease KW - Stroke ultrasound KW - Substantia nigra KW - Ultrasound UR - https://link.springer.com/chapter/10.1007%2F978-3-319-59153-7_21 L2 - https://link.springer.com/chapter/10.1007%2F978-3-319-59153-7_21 N2 - 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. ER -
BLAHUTA, Jiří, Tomáš SOUKUP and 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. \textit{Lecture Notes in Computer Science}. Volume 10305. Cham: Springer Verlag, 2017, p.~236-245. ISBN~978-3-319-59152-0. Available from: https://dx.doi.org/10.1007/978-3-319-59153-7\_{}21.
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