diagnostic standard is a pleural biopsy with subsequent histologic examination of the tissue demonstrating invasion by
the tumor. The diagnostic tissue is obtained through thoracoscopy or open thoracotomy, both being highly invasive
procedures. Thoracocenthesis, or removal of effusion fluid from the pleural space, is a far less invasive procedure that
can provide material for cytological examination. However, it is insufficient to definitively confirm or exclude the
diagnosis of malignant mesothelioma, since tissue invasion cannot be determined. In this study, we present a
computerized method to detect and classify malignant mesothelioma based on the nuclear chromatin distribution from
digital images of mesothelial cells in effusion cytology specimens. Our method aims at determining whether a set of
nuclei belonging to a patient, obtained from effusion fluid images using image segmentation, is benign or malignant, and
has a potential to eliminate the need for tissue biopsy. This method is performed by quantifying chromatin morphology
of cells using the optimal transportation (Kantorovich–Wasserstein) metric in combination with the modified Fisher
discriminant analysis, a k-nearest neighborhood classification, and a simple voting strategy. Our results show that we can
classify the data of 10 different human cases with 100% accuracy after blind cross validation. We conclude that nuclear
structure alone contains enough information to classify the malignant mesothelioma. We also conclude that the
distribution of chromatin seems to be a discriminating feature between nuclei of benign and malignant mesothelioma
cells.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.