Literature DB >> 23366912

Geometric correction of deformed chromosomes for automatic Karyotyping.

Shadab Khan1, Alisha DSouza, João Sanches, Rodrigo Ventura.   

Abstract

Automatic Karyotyping is the process of classifying chromosomes from an unordered karyogram into their respective classes to create an ordered karyogram. Automatic karyotyping algorithms typically perform geometrical correction of deformed chromosomes for feature extraction; these features are used by classifier algorithms for classifying the chromosomes. Karyograms of bone marrow cells are known to have poor image quality. An example of such karyograms is the Lisbon-K(1) (LK(1)) dataset that is used in our work. Thus, to correct the geometrical deformation of chromosomes from LK(1), a robust method to obtain the medial axis of the chromosome was necessary. To address this problem, we developed an algorithm that uses the seed points to make a primary prediction. Subsequently, the algorithm computes the distance of boundary from the predicted point, and the gradients at algorithm-specified points on the boundary to compute two auxiliary predictions. Primary prediction is then corrected using auxiliary predictions, and a final prediction is obtained to be included in the seed region. A medial axis is obtained this way, which is further used for geometrical correction of the chromosomes. This algorithm was found capable of correcting geometrical deformations in even highly distorted chromosomes with forked ends.

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Year:  2012        PMID: 23366912     DOI: 10.1109/EMBC.2012.6346951

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

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Journal:  BMC Bioinformatics       Date:  2013-10-22       Impact factor: 3.169

2.  ChromoEnhancer: An Artificial-Intelligence-Based Tool to Enhance Neoplastic Karyograms as an Aid for Effective Analysis.

Authors:  Yahya Bokhari; Areej Alhareeri; Abdulrhman Aljouie; Aziza Alkhaldi; Mamoon Rashid; Mohammed Alawad; Raghad Alhassnan; Saad Samargandy; Aliakbar Panahi; Wolfgang Heidrich; Tomasz Arodz
Journal:  Cells       Date:  2022-07-20       Impact factor: 7.666

  2 in total

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