NEURAL NETWORK AND CONVOLUTIONAL ALGORITH TO EXTRACT SHAPES BY E-MEDICUS APPLICATION
Tomasz Rymarczyk
tomasz@rymarczyk.com1Research and Development Center, Netrix S.A., Lublin, 2University of Economics and Innovation in Lublin (Poland)
Barbara Stefaniak
Research and Development Center, Netrix S.A., Lublin (Poland)
Przemysław Adamkiewicz
Research and Development Center, Netrix S.A., Lublin (Poland)
Abstract
The solution shows the architecture of the system collecting and analyzing data. There was tried to develop algorithms to image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. With the use of algorithms such as the level set method, neural networks and deep learning methods, it can obtain a quicker diagnosis and automatically marking areas of the interest region in medical images.
Keywords:
image analysis, level set method, artificial intelligence algorithmsReferences
Balla-Arabe S., Gao X.: A Fast and Robust Level Set Method for Image Segmentation Using Fuzzy Clustering and Lattice Boltzmann Method. IEEE Trans Cybern. 43(3)/2013.
Google Scholar
Filipowicz S.F., Rymarczyk T.: The Shape Reconstruction of Unknown Objects for Inverse Problems. Przeglad Elektrotechniczny 88(3A)/2012, 55–57.
Google Scholar
Jajuga K.: Statystyczna teoria rozpoznawania obrazów. PWN, Warszawa 1990.
Google Scholar
Kłosowski G., Rymarczyk T.: Using Neural Networks and Deep Learning Algorithms in Elecrical Impedance Tomography. Informatyka, Automatyka Pomiary w Gospodarce i Ochronie Środowiska (IAPGOŚ) 3/2017, 99–102.
Google Scholar
Kurzyński M.: Rozpoznawanie obiektów. Metody statystyczne. Oficyna Wydawnicza Politechniki Wrocławskiej, Wrocław 1997.
Google Scholar
Li C., Kao C., Gore J. C., Ding Z.: Minimization of Region-Scalable Fitting Energy for Image Segmentation. IEEE Trans. Image Processing 17(10)/2008, 1940–1949.
Google Scholar
Mumford D., Shah J.: Optimal approximation by piecewise smooth functions and associated variational problems. Comm. Pure Appl. Math. 42/1989, 577–685.
Google Scholar
Osher S., Fedkiw R.: Level Set Methods and Dynamic Implicit Surfaces. Springer, New York 2003.
Google Scholar
Osher S., Sethian J.A.: Fronts Propagating with Curvature Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulations. Journal of Computational Physics 79/1988, 12–49.
Google Scholar
Osowski S., Markiewicz T., Kruk M., Kozłowski W.: Metody sztucznej inteligencji do wspomagania diagnostyki patologii tkanek. WAT, Warszawa 2011.
Google Scholar
Polakowski, K., Filipowicz, S.F., Sikora, J., Rymarczyk, T., Quality of imaging in multipath tomography. Przeglad Elektrotechniczny 85(12)/2009, 134–136.
Google Scholar
Polakowski K., Filipowicz S., Sikora J., Rymarczyk T.: Tomography Technology Application for Workflows of Gases Monitoring in The Automotive Systems. Przegląd Elektrotechniczny 84(12)/2008, 227–229.
Google Scholar
Rymarczyk T., Filipowicz S., Sikora J., Polakowski K.: A piecewise-constant minimal partition problem in the image reconstruction. Przegląd Elektrotechniczny 85(12)/2009, 141–143.
Google Scholar
Rymarczyk T., Sikora J., Waleska B.: Coupled Boundary Element Method and Level Set Function for Solving Inverse Problem in EIT. 7th World Congress on Industrial Process Tomography, WCIPT7 2013, 312–319.
Google Scholar
Authors
Tomasz Rymarczyktomasz@rymarczyk.com
1Research and Development Center, Netrix S.A., Lublin, 2University of Economics and Innovation in Lublin Poland
Authors
Barbara StefaniakResearch and Development Center, Netrix S.A., Lublin Poland
Authors
Przemysław AdamkiewiczResearch and Development Center, Netrix S.A., Lublin Poland
Statistics
Abstract views: 209PDF downloads: 132
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Most read articles by the same author(s)
- Grzegorz Kłosowski, Tomasz Rymarczyk, USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 7 No. 3 (2017)
- Tomasz Rymarczyk, Michał Gołąbek, Piotr Lesiak, Andrzej Marciniak, Mirosław Guzik, CONSTRUCTION OF AN ULTRASONIC TOMOGRAPH FOR ANALYSIS OF TECHNOLOGICAL PROCESSES IN THE FIELD OF REFLECTION AND TRANSMISSION WAVES , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Tomasz Rymarczyk, Tomasz Cieplak, Grzegorz Kłosowski, Paweł Rymarczyk, DESIGN OF DATA ANALYSIS SYSTEMS FOR BUSINESS PROCESS AUTOMATION , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 3 (2018)
- Dominik Gnaś, Przemysław Adamkiewicz, INDOOR LOCALIZATION SYSTEM USING UWB , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 12 No. 1 (2022)
- Tomasz Rymarczyk, Bartek Przysucha, Marcin Kowalski, Piotr Bednarczuk, ANALYSIS OF DATA FROM MEASURING SENSORS FOR PREDICTION IN PRODUCTION PROCESS CONTROL SYSTEMS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Tomasz Rymarczyk, Grzegorz Kłosowski, THE USE OF ARTIFICIAL INTELLIGENCE IN AUTOMATED IN-HOUSE LOGISTICS CENTRES , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 1 (2018)
- Tomasz Rymarczyk, Krzysztof Polakowski, Jan Sikora, A NEW CONCEPT OF DISCRETIZATION MODEL FOR IMAGING IMPROVING IN ULTRASOUND TRANSMISSION TOMOGRAPHY , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 9 No. 4 (2019)
- Konrad Niderla, Tomasz Rymarczyk, Jan Sikora, MANUFACTURING PLANNING AND CONTROL SYSTEM USING TOMOGRAPHIC SENSORS , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 8 No. 3 (2018)
- Grzegorz Kłosowski, Tomasz Rymarczyk, APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS IN WALL MOISTURE IDENTIFICATION BY EIT METHOD , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 12 No. 1 (2022)
- Tomasz Rymarczyk, Paweł Tchórzewski, Jan Sikora, COUPLING BOUNDARY ELEMENT METHOD WITH LEVEL SET METHOD TO SOLVE INVERSE PROBLEM , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 7 No. 1 (2017)
