Advanced Imaging

AdvancedImagingPro.com

   

Advanced Imaging Magazine

Updated: January 12th, 2011 09:49 AM CDT

Researching the Brain

Using gamma ray technology to investigate diseases
Images courtesty The Center for Gamma-Ray Imaging
Figure 1. The complete FastSPECT III imaging system, with acquisition/ processing computers. CCD data from all cameras are acquired and processed simultaneously.
Figure 2A. Front view of the FastSPECT III imaging system. A central ring of 10 and two outer rings of five BazookaSPECT detectors focus at a common field of view.
Figure 2B. Side view of the FastSPECT III imaging system. A central ring of 10 and two outer rings of five BazookaSPECT detectors focus at a common field of view.
Advertisement

By Barry Hochfelder

BazookaSPECT comprises a novel combination of an image intensifier, a columnar or structured scintillation material, an optical-coupling system, and any off-the-shelf CCD/CMOS sensor. With amplification of scintillation light prior to the imaging chain, the researchers achieve great flexibility in detector design.

Twenty independent BazookaSPECT gamma-ray detectors acquire projections of a spherical field of view with pinholes selected for desired resolution and sensitivity. Each BazookaSPECT detector comprises a columnar CsI (Tl) scintillator, image-intensifier, optical lens and fast-frame-rate CCD camera operating at 200 frames per second. Data stream back to processing computers via Firewire interfaces, and heavy use of graphics processing units (GPUs) ensures that each frame of data can be processed in real time to extract the images of individual gamma-ray events.

In a white paper, the process is described as frame-parsing. “One algorithm for frame processing uses the following steps:

1. A frame from the CCD is acquired.

2. A median filter is applied to remove hot/noisy pixels.

3. The filtered image is thresholded above the noise, and individual clusters are identified via a fast connected components labeling algorithm.

4. Pixels corresponding to the identified clusters are extracted.

5. Using the associated cluster pixels, the 2D/3D interaction location is estimated optimally using maximum likelihood estimation.”



Subscribe to our RSS Feeds