Neural network for cell image analysis for identification of abnormal cells
US6463438B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 3, 1994 |
| Grant date | Oct 8, 2002 |
| Priority date | — |
| Expiry date | Jun 3, 2014 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30024
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A neural network is used in a system to detect abnormalities in cells, including cancer in bladder tissue cells. The system has an image analysis system for generating data representative of imaging variables from an image of stained cells. The set of data is provided to a neural network which has been trained to detect abnormalities from known tissue cells with respect to the data from the same set of imaging variables. A conventional sigmoid-activated neural network, or alternatively, a hybrid neural network having a combination of sigmoid, gaussian and sinusoidal activation functions may be utilized. The trained neural network applies a set of weight factors obtained during training to the data to classify the unknown tissue cell as normal or abnormal.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.