Rapid On-Site Evaluation Using Artificial Intelligence for Lung Cytopathology

A system and method are presented for applying convolutional neural networks (CNNs) to aid in rapid on-site evaluation cytopathology. Image data are acquired from a biopsy slide. Areas of interest are determined using a first CNN. The image data is segmented into image tiles, and tiles showing the areas of interest are analyzed using a second CNN to assign a histologic category to the slide. The second CNN also utilizes site specific data relating to the biopsy location. Layered image data from multiple focal planes can be acquired of the slide and used as input to the second CNN. Categorized tiles are sorted and presented to a remote computing system for cytopathology determinations, aided by the results of applying the second CNN. Semantic segmentation can also be developed, both as input to the second CNN and as data presented to the remote computer system.