LEVEL SETS AND COMPUTATIONAL INTELLIGENCE ALGORITHMS TO MEDICAL IMAGE ANALYSIS IN E-MEDICUS SYSTEM
Tomasz Rymarczyk
tomasz.rymarczyk@netrix.com.plNetrix S.A., Research and Development Center (Poland)
Abstract
In this work, there were implemented methods to analyze and segmentation medical images by using topological, statistical algorithms and artificial intelligence techniques. The solution shows the architecture of the system collecting and analyzing data. There was tried to develop an algorithm for level set method (LSM) applied to piecewise constant image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. The image segmentation refers to the process of partitioning a digital image into multiple regions. There is typically used to locate objects and boundaries in images. There was also shown an algorithm for analyzing medical images using a neural network MLP.
Keywords:
segmentation, image analysis, level set methodReferences
Argenziano G., Soyer P.H., De Giorgi V., Piccolo D.: Interactive atlas of dermatoscopy, EDRA 2000.
Google Scholar
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
Braun R. P., Rabinovitz H. S.: Dermoscopy of pigmented skin lesions, J Am Acad Dermatol, 52, 2005, 109-121.
Google Scholar
Gdula A., Rymarczyk T.: Application Computational Algorithms for Analysis of Dental Image, WD 2015.
Google Scholar
Jajuga K.: Statystyczna teoria rozpoznawania obrazów, PWN, Warszawa 1990.
Google Scholar
Johr R.H.: Dermoscopy: Alternative melanocytic algorithms-the ABCD rule of dermatoscopy, Menzies scoring method, and 7-point checklist. Clin. DermC.atol. 2002.
Google Scholar
Kamińska J., Winciorek G.: Dermatologia cyfrowa, Cornetis 2008.
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, vol. 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
Ossowski S.: Sieci neuronowe do przetwarzania informacji, Politechnika Warszawska, Warszawa 2006.
Google Scholar
Osowski S., Markiewicz T., Kruk M., Kozłowski W.: Metody sztucznej inteligencji do wspomagania diagnostyki patologii tkanek, WAT, Warszawa 2011.
Google Scholar
Rymarczyk T.: Characterization of the shape of unknown objects by inverse numerical methods, Electrical Review, 7b/2012, 138–140.
Google Scholar
Rymarczyk T., Osior K.: E-Medicus System for Analysis and Images Segmentation, IIPhWD 2013.
Google Scholar
Rymarczyk T., Filipowicz S.F., Sikora J., Polakowski K.: A piecewise-constant minimal partition problem in the image reconstruction, Przegląd Elektrotechniczny, 12/2009, 141–143.
Google Scholar
Sadowski T, Rymarczyk T.: Method for Segmentation Medical Images of Thorax and Detecting Anomalies, WD2014, 2014.
Google Scholar
Sethian J.A.: Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999.
Google Scholar
Stąpor K.: Metody klasyfikacji obiektów w wizji komputerowej. Wydawnictwo Naukowe PWN, Warszawa 2011.
Google Scholar
Stolz W., Braun-Falco O.: Color atlas of dermatoscopy, Blackwell Science, 1994.
Google Scholar
Vese L. Chan T.: A new multiphase level set framework for image segmentation via the Mumford and Shah model, CAM Report 01-25, UCLA Math. Dept., 2001.
Google Scholar
Xiong G., Zhou X., Ji L., Bradley P., Perrimon N., Wong S.: Automated Segmentation of Drosophila RNAi Fluorescence Cellular Images using Deformable Models, IEEE Transactions on Circuits and Systems, Vol. 53, No. 11, 2006, 2415–2424.
Google Scholar
Authors
Tomasz Rymarczyktomasz.rymarczyk@netrix.com.pl
Netrix S.A., Research and Development Center Poland
Statistics
Abstract views: 187PDF downloads: 48
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, 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)
- 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, 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, 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, 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)
- Tomasz Rymarczyk, Jan Sikora, SINGULAR INTEGRATION IN BOUNDARY ELEMENT METHOD FOR HELMHOLTZ EQUATION FORMULATED IN FREQUENCY DOMAIN , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 11 No. 4 (2021)
- Tomasz Rymarczyk, Jan Sikora, SOME MORE ON LOGARITHMIC SINGULARITY INTEGRATION IN BOUNDARY ELEMENT METOD , Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska: Vol. 14 No. 1 (2024)
- 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)