Principle of least commitment in the analysis of chromosome images

James M. Keller; Paul D. Gader; Charles W. Caldwell

doi:10.1117/12.211800

13 June 1995 Principle of least commitment in the analysis of chromosome images

James M. Keller, Paul D. Gader, Charles W. Caldwell

Proceedings Volume 2493, Applications of Fuzzy Logic Technology II; (1995) https://doi.org/10.1117/12.211800
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

The automation of chromosome identification and visualization for a complete cell (karyotyping) has been the subject of considerable research. While rather high classification rates are possible on individual chromosomes, the cell level classification rates are still quite low. We describe a system which uses partial confidence values generated by neural and fuzzy classifiers with optimization to increase the cell level recognition rates. This is consistent with Marr's Principle of Least Commitment for the design of intelligent computer vision algorithms.

Citation Download Citation

James M. Keller, Paul D. Gader, and Charles W. Caldwell "Principle of least commitment in the analysis of chromosome images", Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); https://doi.org/10.1117/12.211800

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

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.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available