Wednesday, August 19, 2015
Mapping Human Pathology
Pathobin is an on-line repository where pathologists can publish and share their pathology images.
Pathology images uploaded to Pathobin can be viewed by anyone using the Leaflet.js mapping library.
You can browse for pathology images on Pathobin using the 'Recent Images' gallery on the site's homepage or from the site index. When you select an image to view on Pathobin a Leaflet map of the pathogen opens. Using the usual Leaflet navigation controls you can pan and zoom the map to view the image in close-up detail.
Created by the NYU School of Medicine the Virtual Microscope uses the Google Maps API to display and navigate scanned slides of microscopic images. Students and faculty members who are logged into the school's Learning Management System can even add markers to the slides to annotate and comment on slide features.
The University of New South Wales is also following in this tradition by using the Google Maps API to create maps of human tissue down to the individual cell. You can already explore the first map of human hip tissue.
This Google Map allows you to explore images captured with a scanning electron microscope. Creating map tiles from the electron microscope images allows the university to create an interactive map of the hip tissue. The result is this Google Map which allows researchers to pan and zoom into details in the microscope images, just as you can with any interactive map.
The Genome Projector is a searchable database browser that uses the Google Maps API to provide a zoomable user interface for molecular biology. The Genome Projector currently contains four views, the Genome map, the Plasmid map, the Pathway map, and DNA walk.
The Genome Projector says that "In molecular biology, looking at reactions and behaviors of specific molecular components in microscopic levels is important. ... Therefore, researchers need a scalable point of view, having access to all of the microscopic, macroscopic, and mesoscopic levels of biological knowledge. Moreover, biological data is highly multi-dimensional by nature, and understanding of the data requires multiple views, layers, or projections ..."