Dissertation
Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Research on Segmentation and Analysis Techniques for Chromosome Microscopic Image

Author YuHaiFeng
Tutor TangRuiChun; BaiFeiXiang
School Ocean University of China
Course Computer technology
Keywords Chromosome Microscopic Image Image segmentation Image analysis
CLC TP391.41
Type Master's thesis
Year 2012
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The treatment and analysis of medical microscopic image is the most commonly used means of modern medical research, Digital medical images has already became the fundamental basis of the doctor to diagnose the illness. Of these digital medical images processing, enhancement and recognition has always been the important applications of computer image processing. Computer image processing technology has already became the development trend of medical microscopic image analysis technology with the superiority of its exactness, objectivity and processing speed. Analysis for chromosome microscopic image is on the basis of the microscopic image digital analysis of the relevant parameters in the microscopic image. Using computers to do all sorts of process of microscopic images can speed up the analysis and processing and insure people the information they need.Selecting a specific suitable segmentation method according to the chromosome images obtained, can make the segmentation results more accurate. This paper introduced on the particle swarm optimization (PSO) based on the traditional C-based average (K mean) clustering segmentation. It solves the problem of falling into the local excellent easily. The method first establishes a color standard of chromosome color image. This guideline will divide chromosome color image into two images automatically:image A and image B. Each sample is regarded as one particle in the particle swarm, based on which, it segments the chromosome color image by C-Means (K mean) clustering algorithm based on PSO. Thus, it solves the problem of local excellent during the segmentation process effectively.In order to solve the computationally intensive problem, it uses Kaman prediction algorithm to predict the iterative cluster center value. To prevent the generation of a larger offset in subsequent iterations of the process, it predicts the value of the cluster center with an equal interval. The result proves that this approach reduces the number of iterations and improves the speed of the operation greatly.In chromosome microscopic image analysis, this paper puts forward a chromosome shape analysis method based on pair-wise geometric histogram (PGH).Firstly, coding the chromosomal shape information as PGH, and then analysis the parameters of the eccentricity and circularity. It can extract and analysis these two parameters quickly and accurately.The experiments shows that the accuracy of the chromosome image analysis has been greatly improved and the method can provide quantitative, accurate and fast diagnostic tools of clinical diagnosis and medical research.

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