Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/229656
Title: Secured system with pattern recognition for biomedical images
Researcher: Gupta, Ranu
Guide(s): Pachauri, Rahul , Singh, Ashutosh K
Keywords: Engineering and Technology,Engineering,Engineering Electrical and Electronic
University: Jaypee University of Engineering and Technology, Guna
Completed Date: 12/01/2019
Abstract: Images play a vital role in field of life whether it is medical, defense, military, bank, surveillance, traffic monitoring, weather forecast, etc. An image itself explains more than the words. Medical images are very important in doctors as well as patient life. Without the images doctors would not have been able to diagnose the disease and would not be able to give proper treatment. There are various diseases in the world but major deaths are due to cardiovascular disease [world health organization (WHO), 2008]. Thus, the aim of this thesis would be to concentrate on the images related to cardiovascular disease like carotid artery. The medical images are taken from different modalities like MRI, CT, Ultrasound, etc. Developing countries like India where major population is from average class and below average class family who could not afford funds for the treatment of the diseases. Ultrasound images are the best solution for it as they are affordable, harmless, easily available and could image most of the cardiovascular diseases. Thus, the aim of the thesis would be to process the ultrasound images. Ultrasound signals suffer from scattering process [Wagner, (1983)] and produces speckle in the image. The speckle in the ultrasound image degrades the quality of the picture and thus makes the doctors to predict the condition of the patient. The speckle present is of multiplicative as well as additive nature [Frost et al., (1982)]. Therefore, the aim of the thesis would be to filter the speckle present in the images. There are various Linear filters like average [Gonzalez and Woods, (2002)]; Frery, et al., (1997); Narayanan and Wahidabanu, (2009)] weighted average, local statistics mean variance filter [Loizou et al., (2005); Loizou et al., (2002); Christodoulou et al., (2002); Lee, (1981a); Lee, (1980); Lee, (1981b); Kondo et al., (1977); Walkup and Choens, (1974); Kuan et al., (1987); Akl et al., (2012)] and non-linear filters like median [Caloope et al., (2004); Pratt, (1978); Loupas et al., (1989)]
Pagination: xxi,124p.
URI: http://hdl.handle.net/10603/229656
Appears in Departments:Department of Electronics and Communication

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01_title.pdfAttached File67.29 kBAdobe PDFView/Open
02_certificate.pdf56.79 kBAdobe PDFView/Open
03_abstract.pdf13.34 kBAdobe PDFView/Open
04_declaration.pdf16.98 kBAdobe PDFView/Open
05_acknowledgement.pdf11.13 kBAdobe PDFView/Open
06_contents.pdf16.37 kBAdobe PDFView/Open
07_list_of_tables.pdf10.28 kBAdobe PDFView/Open
08_list_of_figures.pdf17.06 kBAdobe PDFView/Open
09_abbreviations.pdf9.78 kBAdobe PDFView/Open
10_list_of_symbols.pdf16.04 kBAdobe PDFView/Open
11_chapter1.pdf1.46 MBAdobe PDFView/Open
12_chapter2.pdf601.3 kBAdobe PDFView/Open
13_chapter3.pdf1.28 MBAdobe PDFView/Open
14_chapter4.pdf1.4 MBAdobe PDFView/Open
15_chapter5.pdf646.27 kBAdobe PDFView/Open
16_chapter6.pdf612.83 kBAdobe PDFView/Open
17_chapter7.pdf57.41 kBAdobe PDFView/Open
18_conclusion.pdf31.02 kBAdobe PDFView/Open
19_bibliography.pdf73.84 kBAdobe PDFView/Open
20_list_of_publications.pdf9.57 kBAdobe PDFView/Open


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