Object Motion Analysis for Biomedical Applications
Project Award Date: 0000-00-00
This project addresses two fundamental problems in biomedical image analysis: object motion quantification, and shape change characterization. It will result in powerful new tools to assist researchers interested in studying the biomedical mechanisms responsible for object motion and shape change. There are three phases to this project:
(1) the development of new motion quantification methods,
(2) the development of new shape change characterization methods, and
(3) the evaluation of these techniques by collaborators in Biology and Medicine.
The first phase of this project involves the development of new methods for detecting object motion in biomedcial image sequiences and quantifying this motion. Our objective is to constuct an integrated boundary-based and region-based motion dectection system based on the calculus of variations.
Here, we plan to build on our experience with 2D and 3D deformable object models for image segmentation, multisensor data fusion, and robust optic flow calculation methods. By simultaneously detecting object boundaries and tracking their motion, researchers will be able to quantify the motion of objects or regions of interests in images more reliably.
The second phase of this project involves the development of new methods for characterizing shape change using the motion information obtained above. Shape change analysis (also known as morphometrics) is typically performed based on manually identified biological landmarks. Our objective is to automatically identify visually distinct landmarks which follow the motion field we have calculated. To do so, we plan to make use of multiscale shape analysis applied to object boundaries to identify image landmarks based on their geometric properties. Thus, we will be extending morphometric tools to a wider range of applications.
The third phase of this project involves the evaluation of our motion analysis tools. We have been working with Prof. Max Fiskin and Prof. Elliot Goldstein at the University of Kansas Medical Center (KUMC) on a project to track and quantify the motion of white blood cells (PMNs) in microscopic image sequences. Since PMNs play an important role in fighting infection, the motility of these cells in different patients with different treatments is of great medical interest. In our current system, moving PMN cells are video taped, digitized on a PC, and processed using KUIM software to locate and track moving cells. The movement of individual cells is then statistically analyzed to determine the motility of the population cells. Our future goals are to investigate two fundamental questions:
(1) how PMNs change shape prior and during motion, and
(2) how Ca and pH vary in PMNs as they change shape and move.
Primary Sponsor(s): The Whitaker Foundation, Biomedical Engineering Research Program