Publications

 

Peer-reviewed papers


"
An Automated High Capacity Data Capture and Analysis System for the in vitro Assessment of Leukocyte Adhesion Under Shear-stress Conditions",
by Joseph Low, Debra Killner, and Wade Schuette,
Journal of Immunological Methods 194: 59-70 (1996).


Conferences

"A Data Management System Allowing Multi-Institutional Clinical Trials to Deliver Secure Communication and Good Clinical Laboratory Practice Standards on the World-Wide Web", by R. Wade Schuette MBA, Daniel P. Normolle PhD
Dean E. Brenner MD, and KyungMann Kim PhD .   Delivered at Society for Clinical Trials annual conference, July 9, 1997, Boston MA.


A Novel Quantitative Automated Technique for Identifying and Scoring Stained Regions in Immunohistochemcial specimens with dual stains.

Invited paper for Great Lakes International Imaging and Flow Cytometry conf. 12 Oct 2000, Detroit MI



Public Health -- White Papers (hot-links)

My MPH Capstone talk - on-line patient self-support teams (Johns Hopkins 01-May-2007)

Spectacular teams through active strength, not more SOP's

Multilevel contributing factor analysis of the Crash of Comair 5191 - Lexington Kentucky August 2006 -  A teaching document for safety analysis.




Patents

US Patent 5613013 - R. Wade Schuette, 18-March-1997
"Glass Patterns in Image Alignment and Analysis"

Keywords: image registration, image alignment, image stabilization,
mosaic, montage, feature matching,  pattern recognition, machine vision


This patent describes a new,  very fast (low order) algorithm for automatically matching overlapping portions of two images,  despite x-y translations, rotations, and scale changes (ie affine transformations).  A Glass pattern is a Moire-like pattern obtained by superimposing an image on a transformed version of itself.

One biomedical application would be the automated assembling of captured high-resolution microscopy images into a larger mosaic in real-time,  providing both the resolution and wider field-of-view necessary for automated scoring.  Scoring a larger image overcomes
the selection bias inherent in selection only a particular high-resolution view to be scored.

This is a fundamental patent.  The algorithm applies to any N-dimensional set of arrays (“images”)  which comprise a set of fragments of a larger array (“image”) where the fragments have been scattered,  rotated, skewed, scaled, and reassembly into the original overarching pattern is desired.   It is a basic “data-fusion” patent, with application by extension to finding efficient ways to (re)assemble members of a fragmented, dysfunctional group (back) into a powerful, healthy group with the unity-and-diversity expected.


last update:  1-December-2010