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Title:AVTOMATIZIRANA RAČUNALNIŠKA OBDELAVA FOTOGRAFIJ BETA CELIC TREBUŠNE SLINAVKE PRI MIŠIH
Authors:ID Volgemut, Tadej (Author)
ID Lipovšek, Saška (Mentor) More about this mentor... New window
ID Žalik, Borut (Comentor)
Files:.pdf MAG_Volgemut_Tadej_2015.pdf (2,18 MB)
MD5: FE503FD9E820A31790669DB014655007
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FZV - Faculty of Health Sciences
Abstract:V magistrskem delu smo želeli razviti program za avtomatizirano računalniško obdelavo fotografij, s pomočjo katerega bo možno opravljati meritve premerov poljubnih izstopajočih oblik in njihovih površin. Program bo hkrati omogočal tudi zaporedno analizo na poljubnem območju fotografije, štetje najdenih oblik v neki liniji ter pregled in izvoz rezultatov in statistik. Program smo testirali na meritvah obstoječe raziskave, kjer so proučevali vpliv izbitega Rab3A gena na izločanje inzulina v beta celicah trebušne slinavke pri miših (Lipovšek s sod., 2013). Magistrsko delo služi kot kontrola predhodno opravljenih meritev, program pa omogoča avtomatizirano obdelavo fotografij tudi v drugih raziskavah. Iz članka izhodiščne raziskave in drugih virov smo povzeli teorijo trebušne slinavke, beta celic in inzulina. Predstavili smo anatomijo trebušne slinavke pri miših in jo na kratko primerjali s slinavko pri ljudeh ter nekaterih drugih vrstah. Opisali smo strukturo beta celice, vlogo inzulina ter predstavili vlogo genov iz družine Rab3. Opisali smo digitalno fotografijo in slikovno točko kot njen osnovni gradnik ter predstavili predvidene algoritme za Gaussovo glajenje, pragovno filtriranje ter detekcijo robov. Implementirali smo računalniško aplikacijo, ki omogoča avtomatično analizo fotografij tkivnih rezin trebušne slinavke in dobljene rezultate primerjali z rezultati izhodiščne raziskave. S to nalogo smo želeli ustvariti rešitev, ki bi raziskovalcem olajšala analiziranje mikroskopiranih vzorcev in preverjanje njihovih meritev.
Keywords:trebušna slinavka, beta celica, inzulin, Rab3A, segmentacija, obdelava fotografij, Gaussovo glajenje, pragovno filtriranje, Cannyjev filter
Place of publishing:Maribor
Publisher:[T. Volgemut]
Year of publishing:2015
PID:20.500.12556/DKUM-48174 New window
UDC:004:616.3(043.2)
COBISS.SI-ID:2114468 New window
NUK URN:URN:SI:UM:DK:ZFZH2WYO
Publication date in DKUM:13.07.2015
Views:2182
Downloads:199
Metadata:XML DC-XML DC-RDF
Categories:FZV
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Secondary language

Language:English
Title:AUTOMATED COMPUTER IMAGE PROCESSING OF PANCREAS BETA CELLS IN MICE
Abstract:In this work we wanted to develop the program for automated computer image processing, which will enable measuring of diameters and areas of random shapes. The program will also enable serial segmentation of images in specific region of interest, counting of shapes in defined line and a preview and export of results and statistics. The program was tested on the measurements of existing research about an influence of knocked-out Rab3A gene on insulin secretion in pancreas beta cells in mice (Lipovšek et al., 2013). This master’s degree serves as an assay of prevoiusly made measurements. The program also enables image analysis in other researches. We summarized a theory about pancreas, beta cells and insulin from the article of the existing research and other sources. We described an anatomy of pancreas in mice and made a brief comparison with pancreas in humans and in some other species. We described the strucure of a beta cell, the role of insulin and we described the role of Rab3A family of genes. We described the digital photography and the pixel as the main part of an image. We also described the planned algorithms for implementation of Gaussian blur, thresholding and edge detection. We implemented the computer program, that enabled automated segmentation of images with tissue slices of pancreas and we compared the results with results from the existing research. With this work, we wanted to make a solution, which would help researchers in ther image analysis and in a control of results.
Keywords:pancreas, beta cell, insulin, Rab3A, segmentation, image processing, Gaussian blur, thresholding, Canny edge detection


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