# ALGORITHMS AND PROCESSING ARCHITECTURES FOR TOMOGRAPHY

> **NIH NIH R01** · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · 1987 · $241,381

## Abstract

The principal aim of the research is to provide a method of reconstruction
for tomography (SPECT, PET, TOFPET, X-CT) which represents a substantial
improvement in terms of image quality and instrument design flexibility
over the presently available techniques.  The new proposed method is based
on calculating accurately the response matrix of an imaging instrument,
optimizing its design by mathematical analytic methods and using the final
response matrix as the probability function needed for a maximum likelihood
estimator (MLE) reconstruction algorithm.  In addition, we propose to study
processor architectures for the purpose of designing and building a
prototype processor that can open the way to a future cost-effective
implementation of the MLE algorithm.

The MLE algorithm has been shown to provide substantial improvements in
image quality in PET tomography.  Unfortunately the long computation times
and/or the large amount of storage needed for its implementation make
immediate use and even research on the method impractical.  By providing a
well validated group of programs that calculate the probability functions
for an imaging instrument including effects due to incidence angle and
position, energy resolution and cross-talk, and by developing an effective
method of image analysis, we expect to optimize the MLE imaging problem.
The demonstrated favorable computing power-to-cost ratio of microprocessor
cluster architectures and array processors can then be exploited to
implement the MLE algorithm.

The proposed research program could have a substantial impact in all areas
of medical research and diagnosis which use tomography by providing higher
sensitivity, spatial accuracy, contrast, resolution design flexibility and
better utilization of emitted radiation.  This is particularly more
important now, with the development of new high resolution instruments.

## Key facts

- **NIH application ID:** 3178549
- **Project number:** 5R01CA039501-02
- **Recipient organization:** UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
- **SAM.gov UEI:** ENBLDJUN4N73
- **Principal Investigator:** JORGE LLACER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 1987
- **Award amount:** $241,381
- **Award type:** 5
- **Project period:** 1986-05-01 → 1988-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/3178549

## Citation

> US National Institutes of Health, RePORTER application 3178549, ALGORITHMS AND PROCESSING ARCHITECTURES FOR TOMOGRAPHY (5R01CA039501-02). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/3178549. Licensed CC0.

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