Neural network application in the discrimination of benign from malignant gastric cells

OBJECTIVE: To investigate the potential value of morphometry and neural net works for the discrimination of benign from malignant gastric lesions. STUDY DESIGN: One thousand cells from 19 cases of cancer, 19 cases of gastr itis and 56 cases of ulcer were selected as a training set, and an addition al 4,000 cells from the same cases of cancer, gastritis and nicer were used as a test set. Images of routinely processed gastric smears stained by the Papanicolaou technique were analyzed by a custom-made image analysis syste m. RESULTS: Application of the neural network gave correct classification in 9 6% of benign cells and 89% of malignant cells. CONCLUSION: The results indicate that the use of neural networks and image morphometry may offer useful information concerning Me potential of maligna ncy in gastric cells.