Lasers in Medical Science

, Volume 34, Issue 7, pp 1503–1508 | Cite as

Texture feature extraction of gray-level co-occurrence matrix for metastatic cancer cells using scanned laser pico-projection images

  • Meng-Jia Lian
  • Chih-Ling HuangEmail author
Brief Report


Metastasis is responsible for 90% of all cancer-related deaths in humans, and the development of a rapid and promising solution for an early diagnosis of metastasis is required. The present study proposed a promising method combined with scanned laser pico-projection technique and typical texture feature (i.e., contrast, correlation, energy, entropy, and homogeneity) extraction of gray-level co-occurrence matrix (GLCM) image processing model to classify the low- and high-metastatic cancer cells using five common cancer adenocarcinoma cell line pairs (i.e., HeLa/HeLa-S3, CL1-0/CL1-5, OVTW59-P0/OVTW59-P4, and CE81T-FNlow/CE81T-FNhigh cell lines). Highly metastatic cancer cells essentially have the highest levels of disorder. Both contrast and entropy refer to the degree of disorder, and energy and homogeneity refer to the degree of uniformity. These four texture features can be effective evaluation indexes for disorder in cancer cells responding to metastatic ability. Texture feature extraction forms reflection images, which are recorded with scanned laser pico-projection system; they effectively bridge the gap in information derived from transmission images. The low- and high-metastatic cancer cells are statistically and effectively classified from the texture feature of GLCM through transmission and reflection images taken with scanned laser pico-projection system. In particular, it only requires several seconds after producing a confluent monolayer of cells and achieves the rapid method with a more reliable diagnostic performance for metastatic ability of cancer cells in vitro or ex vivo.


Metastasis Cancer cell Gray-level co-occurrence matrix Scanned laser pico-projection Image analysis 


Funding information

The authors gratefully acknowledge the financial support provided for this study by the Ministry of Science and Technology (MOST) in Taiwan under Grant No. MOST-106-2221-E-037-004. This study is also supported by a grant from the Kaohsiung Medical University Research Foundation (KMU-Q107023).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Approval by Ethical Commission is not needed.

Informed consent

Not applicable since there are no patients involved.


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of DentistryKaohsiung Medical UniversityKaohsiungTaiwan
  2. 2.Center for Fundamental ScienceKaohsiung Medical UniversityKaohsiungTaiwan

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