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1 April 1992 PAPNET TM: an automated cytology screener using image processing and neural networks
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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
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