Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation
Open Access
- 9 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 11 (1), 1-13
- https://doi.org/10.1038/s41598-021-82985-9
Abstract
Classification and characterisation of cellular morphological states are vital for understanding cell differentiation, development, proliferation and diverse pathological conditions. As the onset of morphological changes transpires following genetic alterations in the chromatin configuration inside the nucleus, the nuclear texture as one of the low-level properties if detected and quantified accurately has the potential to provide insights on nuclear organisation and enable early diagnosis and prognosis. This study presents a three dimensional (3D) nuclear texture description method for cell nucleus classification and variation measurement in chromatin patterns on the transition to another phenotypic state. The proposed approach includes third plane information using hyperplanes into the design of the Sorted Random Projections (SRP) texture feature and is evaluated on publicly available 3D image datasets of human fibroblast and human prostate cancer cell lines obtained from the Statistics Online Computational Resource. Results show that 3D SRP and 3D Local Binary Pattern provide better classification results than other feature descriptors. In addition, the proposed metrics based on 3D SRP validate the change in intensity and aggregation of heterochromatin on transition to another state and characterise the intermediate and ultimate phenotypic states.This publication has 48 references indexed in Scilit:
- The Epithelial-to-Mesenchymal Transition (EMT), a Particular CaseMolecular & Cellular Oncology, 2014
- Comparison of 3D Texture-Based Image Descriptors in Fluorescence MicroscopyLecture Notes in Computer Science, 2014
- Three-dimensional solid texture analysis in biomedical imaging: Review and opportunitiesMedical Image Analysis, 2013
- Nuclear Mechanics and Mechanotransduction in Health and DiseaseCurrent Biology, 2013
- CENP-A: the key player behind centromere identity, propagation, and kinetochore assemblyChromosoma, 2012
- Resampling Methods for Meta-Model Validation with Recommendations for Evolutionary ComputationEvolutionary Computation, 2012
- Choosing the kernel parameters for support vector machines by the inter-cluster distance in the feature spacePattern Recognition, 2009
- Nuclear structure in cancer cellsNature Reviews Cancer, 2004
- Survey over image thresholding techniques and quantitative performance evaluationJournal of Electronic Imaging, 2004
- Topographic distance and watershed linesSignal Processing, 1994