Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation.

Affiliation

Rana P(1), Sowmya A(1), Meijering E(1)(2), Song Y(3).
Author information:
(1)School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia.
(2)Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia.
(3)School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia. [Email]

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.