There are a variety of chromosomal abnormalities such as translocation, duplication, deletion, insertion and inversion, which may cause severe diseases, e.g., cancers and birth defects. Multi-color fluorescence in-situ hybridization (M-FISH) is an imaging technique popularly used for simultaneously detecting and visualizing these complex abnormalities in a single hybridization. In spite of the advancement of fluorescence microscopy for chromosomal abnormality detection, the quality of the fluorescence images is still limited, due to the spectral overlap, uneven intensity level across multiple channels, variations of background and inhomogeneous intensity within intra-channels. Therefore, it is critical but challenging to distinguish the different types of chromosomes accurately in order to detect the chromosomal abnormalities from M-FISH images. The main contribution of this dissertation is to develop an M-FISH image analysis pipeline by taking full advantage of spatial and spectral information from M-FISH imaging. In addition, novel image analysis approaches such as the sparse representation are applied in this work. The pipeline starts with the image preprocessing to extract the background to improve the quality of the raw images by low-rank plus group lasso decomposition. Then, the image segmentation is performed by incorporating both spatial and spectral information by total variation (TV) and row-wise constraints. Finally image classification is conducted by considering the structural information of neighboring pixels with a row-wise sparse representation model. In each step, new methods and sophisticated algorithms were developed and compared with several popularly used methods, It shows that (1) the preprocessing model improves the quality of the raw images; (2) the segmentation model outperforms than both fuzzy c-means (FCM) and improved adaptive fuzzy c-means (IAFCM) models in terms of correct ratio and false rate; and (3) the classification model corrects the misclassification to improve the accuracy of chromosomal abnormalities detection, especially for the complex inter-chromosomal rearrangements. / 1 / Jingyao Li

The image processing methodologies that have been actively studied and developed now play a very significant role in the flourishing biotechnology research. This work studies, develops and implements several image processing techniques for M-FISH and cDNA microarray images. In particular, we focus on three important areas: M-FISH image compression, microarray image processing and expression-based classification. Two schemes, embedded M-FISH image coding (EMIC) and Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis, have been introduced for M-FISH image compression and microarray image processing, respectively. In the expression-based classification area, we investigate the relationship between optimal number of features and sample size, either analytically or through simulation, for various classifiers.

The primary focus of this diploma thesis is on marker chromosomes and phenotypically similar human karyotype polymorphisms, variants of short acrocentric arms in particular. The first half provides a very useful review of literature concerning different aspects of both sSMC and human polymorphisms such as their origin, inheritance, associated phenotype, formation and molecular cytogenetic methods that are applied in the process of identification of these aberrations. The methodical emphasis is on FISH and its modifications (e.g. M-FISH, acro M FISH, cen M-FISH) as well as on the CGH methods. The main objective was to test the above-mentioned methods and state their limitations and applications. Thus, in the other half we provide evaluations of commonly used methods and introduce new strategies that could be implemented to make the identification of these additional chromosomes or satellite translocations more effective. All the conclusions are based on the analysis of 7 patients with sSMC and 4 patients with variants involving acrocentric NOR regions. The results of our thorough research into their karyotypes have been compared with similar findings in the literature. Last but not least, we tried to establish a link between observed abnormalities and the type of a chromosomal aberration at hand.