Adaptive Compositing and Navigation of Variable Resolution Images

Abstract

We present a new, high‐quality compositing pipeline and navigation approach for variable resolution imagery. The motivation of this work is to explore the use of variable resolution images as a quick and accessible alternative to traditional gigapixel mosaics. Instead of the common tedious acquisition of many images using specialized hardware, variable resolution images can achieve similarly deep zooms as large mosaics, but with only a handful of images. For this approach to be a viable alternative, the state‐of‐the‐art in variable resolution compositing needs to be improved to match the high‐quality approaches commonly used in mosaic compositing. To this end, we provide a novel, variable resolution mosaic seam calculation and gradient domain color correction. This approach includes a new priority order graph cuts computation along with a practical data structure to keep memory overhead low. In addition, navigating variable resolution images is challenging, especially at the zoom factors targeted in this work. To address this challenge, we introduce a new image interaction for variable resolution imagery: a pan that automatically, and smoothly, hugs available resolution. Finally, we provide several real‐world examples of our approach producing high‐quality variable resolution mosaics with deep zooms typically associated with gigapixel photography.

Whole slide image data utilization informed by digital diagnosis patterns

“…There have also been studies on user interaction in digital pathology with multi-resolution viewers 19 , 23 , 24 , 25 and eyetracking; 26 however, to our knowledge, this is the first application of using pathologists’ interactions with digital slides to adaptively alter whole slide image resolution for storage and subsequent secondary review. There has also been previous work on compositing several images of differing zoom factors into a single VRI, 27 but this is the first application of such variable resolution imaging in pathology. With our approach, pathologist diagnostic behavior determines the image resolution across the specimen area and allows us to reduce whole slide image data sizes while maintaining the relevant information to the diagnosis.…”