The human chromosome metaspread images are used to generate the karyogram that is used for the diagnosis of the genetic defects. The genetic defects occur due to variation in either the structure of the chromosomes or the number of chromosomes present in the cell. The human chromosome metaspread image selection process is very critical in the karyogram generation task. It is very tedious and time-consuming process and is generally done manually by an expert cytogeneticist. The manual selection results may be biased, and it is possible that the whole search space is not explored to find the best metaspread image. The mood of the cytogeneticist will also greatly affect the selection results. So there is a strong need to automate the process of human chromosome metaspread image selection process. The proposed approach ranks the metaspread images based upon the quality score that is calculated using the count of the chromosomes of various orientations present in the metaspread image. The ranking has been done based upon ordinal ranking process, wherein a unique rank is assigned to each image based upon a set of rules. The rule base aids in the tiebreaking process in case the same quality score is derived for more than one metaspread image. The decision-making process of the expert cytogeneticist has been emulated by using a set of if–then rules. The proposed technique helps to select the best metaspread image, by exploring the complete set of images that can be used for the karyogram generation.
Knowledge and Information Systems – Springer Journals
Published: Feb 14, 2017
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