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Journal of Medical Imaging • Open Access • new

Feature analysis of cell nuclear chromatin distribution in support of cervical cytology
Author(s): Hideki Komagata; Takaya Ichimura; Yasuka Matsuta; Masahiro Ishikawa; Kazuma Shinoda; Naoki Kobayashi; Atsushi Sasaki

Paper Abstract

Cytology, a method of estimating cancer or cellular atypia from microscopic images of scraped specimens, is used according to the pathologist’s experience to diagnose cases based on the degree of structural changes and atypia. Several methods of cell feature quantification, including nuclear size, nuclear shape, cytoplasm size, and chromatin texture, have been studied. We focus on chromatin distribution in the cell nucleus and propose new feature values that indicate the chromatin complexity, spreading, and bias, including convex hull ratio on multiple binary images, intensity distribution from the gravity center, and tangential component intensity and texture biases. The characteristics and cellular classification accuracies of the proposed features were verified through experiments using cervical smear samples, for which clear nuclear morphologic diagnostic criteria are available. In this experiment, we also used a stepwise support vector machine to create a machine learning model and a cross-validation algorithm with which to derive identification accuracy. Our results demonstrate the effectiveness of our proposed feature values.

Paper Details

Date Published: 17 October 2017
PDF: 11 pages
J. Med. Imag. 4(4) 047501 doi: 10.1117/1.JMI.4.4.047501
Published in: Journal of Medical Imaging Volume 4, Issue 4
Show Author Affiliations
Hideki Komagata, Saitama Medical Univ. (Japan)
Takaya Ichimura, Saitama Medical Univ. (Japan)
Yasuka Matsuta, Saitama Red Cross Hospital (Japan)
Masahiro Ishikawa, Saitama Medical Univ. (Japan)
Kazuma Shinoda, Utsunomiya Univ. (Japan)
Naoki Kobayashi, Saitama Medical Univ. (Japan)
Atsushi Sasaki, Saitama Medical Univ. (Japan)

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