Literature survey of chromosomes classification and anomaly detection using machine learning algorithms

2nd International conference on Advances in Mechanical Engineering

Nimitha, N.^1 ; Arun, C.^1 ; Puvaneswari, A.S.^1 ; Paninila, B.^1 ; Pavithra, V.P.^1 ; Pavithra, B.^1

Department of ECE, R.M.K College of Engineering and Technology, Chennai, India^1

关键词: Anomaly detection;    Banded chromosomes;    Bilateral filters;    Chromosomal abnormalities;    Classification technique;    Fuzzy C mean;    Literature survey;    Touching chromosomes;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/402/1/012194/pdf
DOI  :  10.1088/1757-899X/402/1/012194

来源: IOP

【 摘 要 】

Detection of chromosomal anomaly is done to prevent diseases at early stage. Karyotyping is the oldest manual method of detecting chromosomal abnormalities by dividing the chromosomes in laboratories. Reviews on karyotyping and previous other classification reviews on classification state that classifications were not extremely accurate. Some of them needed operator's interaction in the identification and separation of overlapping or touching chromosomes. They also didnot work properly for acrocentric, slanted, curved, banded chromosomes. Some works only for particular chromosomal anomaly. In our paper we are proposing chromosomal anomaly detection through various classification techniques to reach out the best accuracy.