ANALYSIS OF THE EFFECTIVENESS OF SELECTED SEGMENTATION METHODS OF ANATOMICAL BRAIN STRUCTURES
Róża Dzierżak
r.dzierzak@pollub.plLublin University of Technology, Institute of Electronics and Information Technology (Poland)
Magdalena Michalska
Lublin University of Technology, Institute of Electronics and Information Technology (Poland)
Abstract
An important aspect of analysis medical images is acknowledging the role of the segmentation process of individual anatomical structures. This process allows to show the most important diagnostic details. Owing to the segmentation the areas of interest (ROI) it is possible to adapt the methods of further image analysis considering the specification of selected elements. This process has been widely used in medical diagnostics. The article presents the use of segmentation by thresholding, segmentation by region growth and by edge detection to extract the parts of the human brain the user is interested in. The series of MRI (magnetic resonance imaging) images were used. The aim of the research was to develop the methods that would allow comparing the effectiveness various types of anatomical brain structures’ segmentation in two dimensions. The above methods present the different impact that selected types of segmentation, masks or parameters have on the most accurate depiction of a selected human brain element.
Keywords:
brain imaging, image segmentation, magnetic resonance imagingReferences
Avrunin O. G., Tymkovych M. Y., Moskovko S. P., Romanyuk S. O., Kotyra A., Smailova S.: Using a priori data for segmentation anatomical structures of the brain. Przegląd Elektrotechniczny 93/2017, 102–105.
Google Scholar
Bellon O. R., Silva L.: New improvements to range image segmentation by edge detection. IEEE Signal Processing Letters 9/2002, 43–45.
Google Scholar
Bernstein M. A., King K. F., Xiadhong J. Z.: Handbook of MRI pulse sequences. Amsterdam. Elsevier, 2004.
Google Scholar
Boskovitz V., Guterman H.: An adaptive neuro-fuzzy system for automatic image segmentation and edge detection. IEEE Transactions on Fuzzy Systems 10/2002, 247–262.
Google Scholar
Hidayatullah R. R., Sigit R., Wasista S.: Segmentation of head CT-scan to calculate percentage of brain hemorrhage volume. Knowledge Creation and Intelligent Computing (IES-KCIC), IEEE, 2017, [DOI: 10.1109/KCIC.2017.8228603].
Google Scholar
Kaganami H. G., Beiji Z.: Region-Based Segmentation versus Edge Detection. Intelligent Information Hiding and Multimedia Signal Processing IIH-MSP'09. Fifth International Conference, 2009.
Google Scholar
Rebouças E. S., Braga A. M., Sarmento R. M.: Level Set Based on Brain Radiological Densities for Stroke Segmentation in CT Images. Computer-Based Medical Systems (CBMS), IEEE 2017 [DOI: 10.1109/CBMS.2017.172]
Google Scholar
Sharma N., Aggarwal L. M.: Automated medical image segmentation techniques. J. Med. Phys. 35/2010, 3–14.
Google Scholar
Suri J. S., Setarehdan S. K., Singh S.: Advanced Algorithmic Approaches to Medical Image Segmentation. Springer, 2002.
Google Scholar
Tadeusiewicz R., Korohoda P.: Komputerowa analiza i przetwarzanie obrazów. Wydawnictwo Postępu Telekomunikacji, Kraków 1997.
Google Scholar
Tadeusiewicz R., Śmietański J.: Pozyskiwanie obrazów medycznych oraz ich przetwarzanie, analiza, automatyczne rozpoznawanie i diagnostyczna interpretacja. Wydawnictwo Studenckiego Towarzystwa Naukowego, Kraków 2011.
Google Scholar
Ulagamuthalvi V., Kulanthaivel G.: An novel approach for segmentation using brain images. International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT ), IEEE, 2017.
Google Scholar
Wróbel Z., Koprowski R.: Praktyka przetwarzania obrazów z zadaniami w programie Matlab. Akademicka Oficyna Wydawnicza EXIT, Warszawa 2012.
Google Scholar
Yahiaoui A. F. Z., Bessaid A.: Segmentation of ischemic stroke area from CT brain images, Signal, Image, Video and Communications (ISIVC), IEEE 2017 [DOI: 10.1109/ISIVC.2016.7893954].
Google Scholar
Authors
Róża Dzierżakr.dzierzak@pollub.pl
Lublin University of Technology, Institute of Electronics and Information Technology Poland
Authors
Magdalena MichalskaLublin University of Technology, Institute of Electronics and Information Technology Poland
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