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Segmentation and Contrasting in Different Biomedical Imaging Applications

Abstract : Advancement in Image Acquisition Equipment and progress in Image Processing Methods have brought the mathematicians and computer scientists into areas which are of huge importance for physicians and biologists. Early diagnosis of diseases like blindness, cancer and digestive problems have been areas of interest in medicine. Development of Laser Photon Microscopy and other advanced equipment already provides a good idea of very interesting characteristics of the object being viewed. Still certain images are not suitable to extract sufficient information out of that image. Image Processing methods have been providing good support to provide useful information about the objects of interest in these biological images. Fast computational methods allow complete analysis, in a very short time, of a series of images, providing a reasonably good idea about the desired characteristics. The thesis covers application of these methods in 3 series of images intended for 3 different types of diagnosis or inference. Firstly, Images of RP-mutated retina were treated for detection of rods, where there were no cones present. The software was able to detect and count the number of cones in each frame. Secondly, a gastrulation process in drosophila was studied to observe any mitosis and results were consistent with recent research. Finally, another series of images were treated where biological cells were observed to undergo mitosis. The source was a video from a photon laser microscope. In this video, objects of interest were biological cells. The idea was to track the cells if they undergo mitosis. Cell position, spacing and sometimes contour of the cell membrane are broadly the factors limiting the accuracy in this video. Appropriate method of image enhancement and segmentation were chosen to develop a computational method to observe this mitosis. Cases where human intervention may be required have been proposed to eliminate any false inference.
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Submitted on : Wednesday, October 31, 2012 - 12:12:16 PM
Last modification on : Wednesday, September 28, 2022 - 4:20:11 PM
Long-term archiving on: : Friday, February 1, 2013 - 3:38:38 AM


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  • HAL Id : tel-00747430, version 1




Muhammad Tayyab. Segmentation and Contrasting in Different Biomedical Imaging Applications. Human health and pathology. Université de Grenoble, 2012. English. ⟨NNT : 2012GRENS009⟩. ⟨tel-00747430⟩



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