Dynamic single photon emission computed tomography (dSPECT) provides time-varying spatial information about changes of tracer distribution in the body from data acquired using a standard (single slow rotation) protocol. Variations of tracer distribution observed in the images might be due to physiological processes in the body, but may also stem from reconstruction artefacts. These two possibilities are not easily separated because of the highly underdetermined nature of the dynamic reconstruction problem. Since it is expected that temporal changes in tracer distribution may carry important diagnostic information, the analysis of dynamic SPECT images should consider and use this additional information.
In this paper we present a segmentation scheme for aggregating voxels with similar time activity curves (TACs). Voxel aggregates are created through region merging based on a similarity criterion on a reduced set of features, which is derived after transformation into eigenspace. Region merging was carried out on dSPECT images from simulated and patient myocardial perfusion studies using various stopping criteria and ranges of accumulated variances in eigenspace. Results indicate that segmentation clearly separates heart and liver tissues from the background. The segmentation quality did not change significantly if more than 99% of the variance was incorporated into the feature vector. The heart behaviour followed an expected exponential decay curve while some variation of time behaviour in liver was observed. Scatter artefacts from photons originating from liver could be identified in long as well as in short studies.
Conventional methods to diagnose and follow treatment of Multiple Sclerosis require radiologists and technicians to compare current images with older images of a particular patient, on a slic-by-slice basis. Although there has been progress in creating 3D displays of medical images, little attempt has been made to design visual tools that emphasize change over time. We implemented several ideas that attempt to address this deficiency. In one approach, isosurfaces of segmented lesions at each time step were displayed either on the same image (each time step in a different color), or consecutively in an animation. In a second approach, voxel- wise differences between time steps were calculated and displayed statically using ray casting. Animation was used to show cumulative changes over time. Finally, in a method borrowed from computational fluid dynamics (CFD), glyphs (small arrow-like objects) were rendered with a surface model of the lesions to indicate changes at localized points.
Conference Committee Involvement (2)
Visualization and Data Analysis 2011
24 January 2011 | San Francisco Airport, California, United States
Wavelets XII
26 August 2007 | San Diego, California, United States
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.