Sru Biosystems, Inc.

The General Hospital Corporation

X-body, Inc.

William C Karl

Peter Li

Homer Pien

Brian T Cunningham

Derek Puff

Lance Gavin Laing

Bo Lin

Timothy Smith

Thomas J Brady

Lara Madison

Christine C Genick

Zhuangli Liang

Performing high-resolution determination of the relative shift of the spectral properties of a biosensor. The shift in the resonance peak of the biosensor is indicative of the amount of material bound to the surface of the biosensor. A preferred biosensor is a Guided Mode Resonant Filter Biosensor (GMRFB). In one aspect of the invention, curve fitting is used to determine the relative location of the spectrum of the unexposed biosensor with respect to those spectra that are altered (e.g., shifted) by the presence of materials bound to the surface of the biosensor. In an alternative embodiment, the cross correlation function is used to detect spectral peak offsets between a reference spectrum and a spectrum measured from an exposed biosensor. In yet another alternative, maximal likelihood estimation techniques are used to determine the spectral shift or offs.

Method and apparatus for biosensor spectral shift detection

The invention provides methods of detecting a change in cell growth patterns, methods of screening many different antibodies in one receptacle, and methods of detecting specific binding of an antibody to a protein or cell, wherein the antibody is in a mixture of many different antibodies.

Methods for screening cells and antibodies

In one aspect, the invention is a method of medical image processing. The method includes receiving data representing a medical image. The method also includes generating the medical image based on a model. The model characterizes the medical image as a composition of at least two components having processing constraints.

Medical image processing

In one aspect, the invention is a method to reduce a blooming effect of a bright object in a medical image generated from a low-dose imaging system. The method includes characterizing an ideal image as a composition of a first component and a second component. The first component is characterized by a first function and the second component is characterized by a second function. The method also includes minimizing the first function and the second function using a smoothing process and generating the medical image based on the minimizing.

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North Andover, MA, United States of America

William C Karl