WholeSlide for IPAD
10/11/2011 Version 1.05 has been pushed to the app store, addressing minor bugs and adding support for the OpenConnectome datasets. Available on the App Store
The WholeSlide iPad app was developed to enable rapid access and rich interaction with large (1 gigapixel + ) wholeslide images hosted online. The app allows users to natively zoom into a wealth of image types: from neuroanatomy and developmental biology to pathology and histology resources

Figure 1. Main Menu, Set Browser, and Tile Chooser.
Basic usage
Select a site from the main menu to show a list of available data sets. Selecting a dataset will present the list of wholeslide images for that set available to view. Sites and sets are organized based on their own internal structure. Some sites are grouped by folder while others are searchable. Selecting an image will load it into the viewer.
Wholeslide from Rich Stoner on Vimeo.
Controls
The WholeSlide App provides tools to interact with wholeslide images on the iPad. Individual tools are toggled on and off using the buttons located immediately to the right of the Tile chooser. Tools can be dragged around the screen using their top handle.

Image Metadata: Here you will find pertinent slide data, including species, stain, native resolution, and attribution. We are limited by the information made available via each independent site and are working to increase the depth and breadth of this content.

Image Adjustment: Here you will find controls to adjust the bright, contrast, and RGB windows of the image. Thanks to the processing power of the iPad, we are able to perform these adjustments in real-time on the device itself. The RGB windows allow you to scale the relatively red, green, and blue channels, but the easiest way to understand how the RGB windows function is to try them yourself.

Navigation: Here you will find a thumbnail of the current image, the effective magnification in screen pixels, and a slider pad to quickly move between images within a dataset.
Adding/Remove data
The WholeSlide application contains links to over 70 Terabytes of image data from the start. However, many researchers and clinicians have their data on University-run image servers. Users can add custom sites and data sets within the app itself. We currently support Zoomify-compatible single tiles and sites that provide an RSS feed of the available tiles.
- Allen Brain Atlas - Comprehensive Mouse Brain Atlas
- UC Davis Brain Maps - 60 Terabytes of wholeslide stacks from many organisms
- CSHL Zebrafinch Atlas - Nissl and Myelin stained orthogonal views
- Aperio SlideScanner Examples - Expansive collection of high-quality wholeslide images
- WormAtlas Virtual Worm - C. Elegans anatomic reference
Below are a list of sites tested in the app. This is not a comprehensive list but will demonstrate the variety of wholeslide images available on the web, all found via a simple google search. To add, copy/paste the RSS feed URL into the wholeslide app. Note: Site availability and performance will vary based on geographic proximity.
- The Rosai Collection - Juan Rosai's collection of surgical pathology seminars (1945 - Present) RSS Feed
- University of Michigan Teaching Collection - Virtual slide list for Medical Histology Course RSS Feed
- University of Michigan Collection 2 - Assorted pathology. RSS Feed
- University of Leeds - Pathology teaching collection RSS Feed
- Heidelberg University - Pathology teaching collection RSS Feed
- Zurich University - ScanScope images RSS Feed
- UNC - Assorted images RSS Feed
- USCAP - Extensive pathology collection and reference RSS Feed
- UPMC - Large research collection RSS Feed
Armed Forces Institute of Pathology- Large pathology teaching collection Down.
Questions/Comments
Please direct questions and comments regarding Application use to the WholeSlide google group
If you have an interesting dataset that you would like to have indexed/served through the Wholeslide app, or know of someone who does - please contact us directly at support at wholeslide.com
Acknowledgments
Support and advice: Stephen Larson, Soren Solari, Harvey Karten, David Matthews, Julia Trigeiro, and many more.
Icons by: Glyphish
Built with: TouchJSON/XML, FMDB, OpenCV, ASIHttp, and feedback from StackOverflow.
