Journal of Pathology Informatics Journal of Pathology Informatics
Contact us | Home | Login   |  Users Online: 533  Print this pageEmail this pageSmall font sizeDefault font sizeIncrease font size 


RESEARCH ARTICLE
Year : 2014  |  Volume : 5  |  Issue : 1  |  Page : 19

A vocabulary for the identification and delineation of teratoma tissue components in hematoxylin and eosin-stained samples


1 Massachusetts Institute of Technology Lincoln Laboratory, Boston, MA, USA
2 Department of Biomedical Engineering, Center for Bioimage Informatics, Pittsburgh, USA
3 Department of Mathematics and Statistics, Air Force Institute of Technology, Wright Patterson Air Force Base, OH, USA
4 Department of Obstetrics and Gynecology, Magee-Womens Research Institute and Foundation of the University of Pittsburgh, Pittsburgh, USA
5 Department of Pathology, Children's Hospital of Pittsburgh of the University of Pittsburgh, Pittsburgh, PA, USA
6 Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh; Massachusetts Institute of Technology Lincoln Laboratory, Boston, MA, USA

Correspondence Address:
Michael T McCann
Department of Biomedical Engineering, Center for Bioimage Informatics, Pittsburgh
USA
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2153-3539.135606

Rights and Permissions

We propose a methodology for the design of features mimicking the visual cues used by pathologists when identifying tissues in hematoxylin and eosin (H&E)-stained samples. Background: H&E staining is the gold standard in clinical histology; it is cheap and universally used, producing a vast number of histopathological samples. While pathologists accurately and consistently identify tissues and their pathologies, it is a time-consuming and expensive task, establishing the need for automated algorithms for improved throughput and robustness. Methods: We use an iterative feedback process to design a histopathology vocabulary (HV), a concise set of features that mimic the visual cues used by pathologists, e.g. "cytoplasm color" or "nucleus density." These features are based in histology and understood by both pathologists and engineers. We compare our HV to several generic texture-feature sets in a pixel-level classification algorithm. Results: Results on delineating and identifying tissues in teratoma tumor samples validate our expert knowledge-based approach. Conclusions: The HV can be an effective tool for identifying and delineating teratoma components from images of H&E-stained tissue samples.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed2075    
    Printed57    
    Emailed0    
    PDF Downloaded344    
    Comments [Add]    

Recommend this journal