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Digital image analysis of mitotic chromosomes
Jaroš, Luboš ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
The development in modern medicine has allowed to study human genome and detect predispositions to several diseases. One of very promising techniques is the analysis of human karyotype, i.e., the number and appearance of chromosomes in the cell nucleus. The most important step in the karyotype analysis is the chromosome detection and categorization. In this work, a new algorithm for detection of chromosomes from an image of microscopic DNA sample and their categorization into seven groups was developed. The algorithm was implemented in Matlab. The accuracy of segmentation and classification was tested on a set of images from two databases with 117 and 38 images, respectively. The sensitivity of the developed segmentation reached 88% while the value of positive predictivity of segmentation reached 92%. The success rate of chromosome pairing achieves 77%.
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Digital image analysis of mitotic chromosomes
Danielová, Tereza ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
This master’s thesis is focused on digital image analysis of mitotic chromosomes. It deals with the design of the processing of digital images - from image preprocessing to clasification of each chromosomes, including testing on a set of images. This work introduces used cytogenetic methods, that are used to visualize chromosomes. In its practical part describes morphology operations and clasification procedure. Classification of the chomosomes was divided into 5 groups (A-G). All algorithms were created in the MATLAB program.
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Digital Image Preprocessing Of Mitotic Chromosomes
Jaroš, Luboš
The goal of this work is to develop a novel algorithm for chromosome detection to make the following analysis of human genome easier. The algorithm uses a multiphase detection based on the Otsu and active contour methods. The accuracy validation is tested on samples from the online BioImlab databases.
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Digital image analysis of mitotic chromosomes
Jaroš, Luboš ; Vítek, Martin (referee) ; Škutková, Helena (advisor)
The development in modern medicine has allowed to study human genome and detect predispositions to several diseases. One of very promising techniques is the analysis of human karyotype, i.e., the number and appearance of chromosomes in the cell nucleus. The most important step in the karyotype analysis is the chromosome detection and categorization. In this work, a new algorithm for detection of chromosomes from an image of microscopic DNA sample and their categorization into seven groups was developed. The algorithm was implemented in Matlab. The accuracy of segmentation and classification was tested on a set of images from two databases with 117 and 38 images, respectively. The sensitivity of the developed segmentation reached 88% while the value of positive predictivity of segmentation reached 92%. The success rate of chromosome pairing achieves 77%.
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Digital image analysis of mitotic chromosomes
Danielová, Tereza ; Provazník, Ivo (referee) ; Škutková, Helena (advisor)
This master’s thesis is focused on digital image analysis of mitotic chromosomes. It deals with the design of the processing of digital images - from image preprocessing to clasification of each chromosomes, including testing on a set of images. This work introduces used cytogenetic methods, that are used to visualize chromosomes. In its practical part describes morphology operations and clasification procedure. Classification of the chomosomes was divided into 5 groups (A-G). All algorithms were created in the MATLAB program.
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Digital Image Analysis of Mitotic Chromosomes
Buchta, M.
The present work describes the cytogenetic from the point of view of image processing. We propose an algorithm which is able to treat every aspect of this analysis such as segmentation and separation of chromosomes. Moreover, our algorithm is tested on images of chromosomes labelled with 2 different methods coming from various free databases.
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