PAPNET TM: an automated cytology screener using image processing and neural networks

Randall L. Luck; Robert Tjon-Fo-Sang; Laurie Mango; Joel R. Recht; Eunice Lin; James Knapp

doi:10.1117/12.58066

1 April 1992 PAPNET TM: an automated cytology screener using image processing and neural networks

Randall L. Luck, Robert Tjon-Fo-Sang, Laurie Mango, Joel R. Recht, Eunice Lin, James Knapp

Proceedings Volume 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges; (1992) https://doi.org/10.1117/12.58066
Event: The 20th AIPR Workshop, 1991, McLean, VA, United States

Abstract

The Pap smear is the universally accepted test used for cervical cancer screening. In the United States alone, about 50 to 70 million of these test are done annually. Every one of the tests is done manually be a cytotechnologist looking at cells on a glass slide under a microscope. This paper describes PAPNET, an automated microscope system that combines a high speed image processor and a neural network processor. The image processor performs an algorithmic primary screen of each image. The neural network performs a non-algorithmic secondary classification of candidate cells. The final output of the system is not a diagnosis. Rather it is a display screen of suspicious cells from which a decision about the status of the case can be made.

Citation Download Citation

Randall L. Luck, Robert Tjon-Fo-Sang, Laurie Mango, Joel R. Recht, Eunice Lin, and James Knapp "PAPNET TM: an automated cytology screener using image processing and neural networks", Proc. SPIE 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges, (1 April 1992); https://doi.org/10.1117/12.58066

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