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Unsupervised organization of cervical cells using bright‐field and single‐shot digital holographic microscopy
Author(s) -
Mangal Jyoti,
Monga Rashi,
Mathur Sandeep R.,
Dinda Amit K.,
Joseph Joby,
Ahlawat Sarita,
Khare Kedar
Publication year - 2019
Publication title -
journal of biophotonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 66
eISSN - 1864-0648
pISSN - 1864-063X
DOI - 10.1002/jbio.201800409
Subject(s) - digital holographic microscopy , bright field microscopy , artificial intelligence , microscopy , clinical practice , principal component analysis , computer science , digital pathology , cluster analysis , holography , biomedical engineering , materials science , computer vision , pattern recognition (psychology) , optics , pathology , medicine , physics , family medicine
Abstract We report results on unsupervised organization of cervical cells using microscopy of Pap‐smear samples in brightfield (3‐channel color) as well as high‐resolution quantitative phase imaging modalities. A number of morphological parameters are measured for each of the 1450 cell nuclei (from 10 woman subjects) imaged in this study. The principal component analysis (PCA) methodology applied to this data shows that the cell image clustering performance improves significantly when brightfield as well as phase information is utilized for PCA as compared to when brightfield‐only information is used. The results point to the feasibility of an image‐based tool that will be able to mark suspicious cells for further examination by the pathologist. More importantly, our results suggest that the information in quantitative phase images of cells that is typically not used in clinical practice is valuable for automated cell classification applications in general.