Paper Details

Cytogenetics plays a central role in the detection of chromosomal abnormalities and in the diagnosis of geneticdiseases. The study of human metaphase chromosomes is an important aspect in clinical diagnosis of genetic disorders. Akaryogram is representation of human chromosomes where they are arranged in decreasing order of size and Karyotyping isa set of procedures that produces a karyogram during the metaphase step of the cellular division, called mitosis Many imageprocessing techniques have been developed for chromosomal karyotyping to assist in laboratory diagnosis, they fail toprovide reliable results in segmenting and extracting the centerline of chromosomes due to their shape variability whenplaced on microscope slides. Effective identification of the chromosome outline with its center line provides a basis forfurther operations such as automated chromosome classification and centromere identification. Karyotypin g andchromosome analysis are very useful in biological applications, e.g. disease identification. The very first step of karyotypi ngis the identification of chromosome.Manual karyotyping is tedious, complex and time consuming, as it requires meticulousattention to details and well trained personnel. Automated system gives countless advantages like speed, simplicity andstorage.This method is considered simple and, yet, robust for this purpose. In this project, we aim to build an automatedkaryotyping system for chromosome analysis.In this paper we have discusssed the fundamental problems of classification of human chromosomes and have explained thesolution to the problem.We have given the introduction about the human chromosomes and the basic theory of the algorithmused.AAN has been implemented to classify the chromosomes.

Prachi Vidhate, Nitesh Sonawane, M.P.Sardey, “CHROMOSOME IDENTIFICAION USING ARTIFICIAL NEURAL NETWORK”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 2, Issue 5, pp. 1044-1047, May 2015.