As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
The karyotyping step is essential in the genetic diagnosis process, since it allows the genetician to see and interpret patient’s chromosomes. Today, this step of karyotyping is a time-cost procedure, especially the part that consists in segmenting and classifying the chromosomes by pairs. This paper presents a compartive study of image classification of banded human chromosomes for automated karyotyping (AKS), by using classifier ensembles. The goal of this contribution is to propose and evaluate a solution to automate the karyotyping, from microscope images to the obtention of the classified chromosomes. For this purpose, we have evaluated several approaches based on classifier ensembles trying to find a solution that shows better trade-off between accuracy and computational cost.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.