AIMC Topic: Karyotyping
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Mathematical approach for segmenting chromosome clusters in metaspread images.
Experimental cell research
Jun 9, 2022
Karyotyping is an examination that helps in detecting chromosomal abnormalities. Chromosome analysis is a very challenging task which requires various steps to obtain a karyotype. The challenges associated with chromosome analysis are overlapping and...
DeepACEv2: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks.
IEEE transactions on medical imaging
Nov 30, 2020
Chromosome enumeration is an essential but tedious procedure in karyotyping analysis. To automate the enumeration process, we develop a chromosome enumeration framework, DeepACEv2, based on the region based object detection scheme. The framework is d...
Varifocal-Net: A Chromosome Classification Approach Using Deep Convolutional Networks.
IEEE transactions on medical imaging
Mar 19, 2019
Chromosome classification is critical for karyotyping in abnormality diagnosis. To expedite the diagnosis, we present a novel method named Varifocal-Net for simultaneous classification of chromosome's type and polarity using deep convolutional networ...
The mutational oncoprint of recurrent cytogenetic abnormalities in adult patients with de novo acute myeloid leukemia.
Leukemia
Mar 24, 2017
Recurrent chromosomal abnormalities and gene mutations detected at the time of diagnosis of acute myeloid leukemia (AML) are associated with particular disease features, treatment response and survival of AML patients, and are used to denote specific...
An Integral R-Banded Karyotype Analysis System of Bone Marrow Metaphases Based on Deep Learning.
Archives of pathology & laboratory medicine
Aug 1, 2024
CONTEXT.—: Conventional karyotype analysis, which provides comprehensive cytogenetic information, plays a significant role in the diagnosis and risk stratification of hematologic neoplasms. The main limitations of this approach include long turnaroun...
[Application of convolutional neural networks for the classification of metaphase chromosomes].
Zhonghua yi xue yi chuan xue za zhi = Zhonghua yixue yichuanxue zazhi = Chinese journal of medical genetics
Mar 10, 2024
OBJECTIVE: To train a deep convolutional neural networks (CNN) using a labeled data set to classify the metaphase chromosomes and test its accuracy for chromosomal identification.
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