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Adler - Green - 2026

Mentor: Stephen Adler, PhD | stephen.adler@nih.gov
Lab
MIB Physics Lab, Clinical Research Directorate (CRD), Frederick National Laboratory for Cancer Research
NCI
Mentor: Michael Green | greenmich@mail.nih.gov
Lab
MIB Physics Lab, Clinical Research Directorate (CRD), Frederick National Laboratory for Cancer Research
NCI

Monte Carlo Simulation of a Collimator-less SPECT Imaging Device with Artificial Intelligence Image Reconstruction

In vivo imaging of biologically active compounds labeled with single photon-emitting radioisotopes is today a major medical diagnostic technology used in millions of patient studies around the world every year.  However, the essential physics underlying single photon imaging, used in single photon emission computed tomography (SPECT) scanners, which use external collimators to form images of single photon containing objects, has not changed significantly in more than 50 years.  This project intends to explore alternatives to this method that can potentially increase detection efficiency (and reduce patient radiation dose) by orders of magnitude and possibly create other performance benefits.

The student will work with staff scientists to build an in silico model of a SPECT scanner which has no collimator. This will involve designing different detector arrays and evaluating their response to radioactive source distributions within the field of view of the scanner using existing physics simulation packages. The goal is to compare outputs from various detector array designs against artificial intelligence (AI) reconstruction accuracy. An optimal imaging system emerging from this work could have a significant impact on both the clinical and research applications of SPECT.

With mentorship throughout the project, the student will:

  1. Learn the basic principles of SPECT imaging.
  2. Learn how to run a single particle tracking event simulator called GEANT 4 using the TOPAS user interface.
  3. Design different detector array geometries and use them as input to the simulation system.
  4. Work with our inhouse AI expert to generate data sets to train a deep learning neural network to reconstruct images.
  5. Validate SPECT scanner/detector array system designs by comparing AI reconstructions of simulated test objects to the known distributions in these objects and by comparison with collimated SPECT systems currently used in nuclear medicine departments.

Environment:
The student will be embedded with the physics team of the NCI/Molecular Imaging Program physics laboratory. The student will be exposed to the ongoing work of the physics lab which includes radiation imaging detector development, precision radiation measurement systems, digital autoradiography and other types of radiation imaging and detection instrumentation development. The laboratory is housed in the NIH Clinical Center, the world’s largest hospital dedicated exclusively to clinical research, located on the main Bethesda campus. Students will have exposure to a wide range of career paths and training levels, including postbaccalaureate fellows, postdoctoral researchers, staff scientists, and clinician-investigators.