Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images
Joint Authors
Hamamoto, K.
Win, Khin Yadanar
Choomchuay, Somsak
Raveesunthornkiat, Manasanan
Source
Journal of Healthcare Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-12
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Automated cell nuclei segmentation is the most crucial step toward the implementation of a computer-aided diagnosis system for cancer cells.
Studies on the automated analysis of cytology pleural effusion images are few because of the lack of reliable cell nuclei segmentation methods.
Therefore, this paper presents a comparative study of twelve nuclei segmentation methods for cytology pleural effusion images.
Each method involves three main steps: preprocessing, segmentation, and postprocessing.
The preprocessing and segmentation stages help enhancing the image quality and extracting the nuclei regions from the rest of the image, respectively.
The postprocessing stage helps in refining the segmented nuclei and removing false findings.
The segmentation methods are quantitatively evaluated for 35 cytology images of pleural effusion by computing five performance metrics.
The evaluation results show that the segmentation performances of the Otsu, k-means, mean shift, Chan–Vese, and graph cut methods are 94, 94, 95, 94, and 93%, respectively, with high abnormal nuclei detection rates.
The average computational times per image are 1.08, 36.62, 50.18, 330, and 44.03 seconds, respectively.
The findings of this study will be useful for current and potential future studies on cytology images of pleural effusion.
American Psychological Association (APA)
Win, Khin Yadanar& Choomchuay, Somsak& Hamamoto, K.& Raveesunthornkiat, Manasanan. 2018. Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images. Journal of Healthcare Engineering،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1191370
Modern Language Association (MLA)
Win, Khin Yadanar…[et al.]. Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images. Journal of Healthcare Engineering No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1191370
American Medical Association (AMA)
Win, Khin Yadanar& Choomchuay, Somsak& Hamamoto, K.& Raveesunthornkiat, Manasanan. Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images. Journal of Healthcare Engineering. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1191370
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191370