Cancer Image Quantification with and Without, Expensive Whole Slide Imaging Scanners

Abstract

Automated analysis of digitized pathology images in tele-health applications can have a transformative impact on under-served communities in the developing world. However, the vast majority of existing image analysis algorithms are trained on slide images acquired via expensive Whole-Slide-Imaging (WSI) scanners. High scanner cost is a key bottleneck preventing large-scale adoption of digital pathology in developing countries. In this work, we investigate the viability of automated analysis of slide images captured from the eyepiece of a microscope via a smart phone. The mitosis detection application is considered as a use case.Results indicate performance degradation when using (lower-quality) smartphone images; as expected. However, the performance gap is not too wide (F1-score smartphone=0.65, F1-score WSI=0.70) demonstrating that smartphones could potentially be employed as image acquisition devices for digital pathology at locations where expensive scanners are not available.