Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 19, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

Published on: April 8, 2019

Statistical LOR estimation for a high-resolution dMiCE PET detector.

Kyle M Champley1, Thomas K Lewellen, Lawrence R MacDonald

  • 1Department of Radiology, University of Washington, Seattle, WA, USA. champlk@u.washington.edu

Physics in Medicine and Biology
|October 8, 2009
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

MRI-Based radiomic signature for predicting pathologic treatment response to neoadjuvant chemoradiotherapy and radioimmunotherapy in soft tissue sarcoma.

Skeletal radiology·2026
Same author

Mature Outcomes and Patterns of Failure in the Phase II FLARE-RT Trial of Biological Image-guided and Risk-Adaptive Chemoradiation for Unresectable NSCLC.

Clinical cancer research : an official journal of the American Association for Cancer Research·2026
Same author

Accuracy comparison of 4D computed tomography (4DCT) and 4D cone beam computed tomography (4DCBCT).

International journal of medical physics, clinical engineering and radiation oncology·2026
Same author

Generative Modeling for Interpretable Anomaly Detection in Medical Imaging: Applications in Failure Detection and Data Curation.

Bioengineering (Basel, Switzerland)·2025
Same author

Consistent performance between medical experts and non-expert readers in forced-choice lesion-detection tasks with PET images.

Medical physics·2025
Same author

Radiomics Quality Score 2.0: towards radiomics readiness levels and clinical translation for personalized medicine.

Nature reviews. Clinical oncology·2025
Same journal

Effective contrast-enhanced preprocessing for intracranial artery segmentation in digital subtraction angiography.

Physics in medicine and biology·2026
Same journal

Improving Plan Quality in Adaptive Proton Therapy Using an Interactive Dose Modification Tool.

Physics in medicine and biology·2026
Same journal

Technical Note: Real-Time MLC Control and Latency Measurement Optimization with External Verification.

Physics in medicine and biology·2026
Same journal

Fetus-Specific Hematopoietic Stem Cell Dosimetry Framework for Leukemia-Relevant Target Cells During Prenatal Development.

Physics in medicine and biology·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
See all related articles

We developed a statistical line of response (LOR) estimator for positron emission tomography (PET) detectors. This new method significantly improves the accuracy of interaction point estimation compared to traditional Anger logic.

Area of Science:

  • Medical Imaging
  • Nuclear Physics
  • Detector Technology

Background:

  • Positron Emission Tomography (PET) relies on accurately determining photon interaction points.
  • Current methods like Anger logic have limitations in precision, especially with complex detector designs.
  • Depth of Interaction (DOI) capability is crucial for high-resolution PET imaging.

Purpose of the Study:

  • To develop a novel statistical Line of Response (LOR) estimator for 3D interaction positions in PET detectors.
  • To improve the accuracy of photon interaction point estimation, particularly in detectors with Depth of Interaction (DOI) capability.
  • To provide a more robust algorithm capable of handling multiple photon interactions within the detector module.

Main Methods:

  • Developed a statistical Line of Response (LOR) estimator based on conditional expectation of interaction points.

Related Experiment Videos

Last Updated: Jun 19, 2026

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster (Nephrops norvegicus)

Published on: April 8, 2019

  • Utilized probability density functions of light collection and photon interaction kinetics models.
  • Incorporated a novel Depth of Interaction (DOI) measurement technique using dual-layer, adjacent detector elements (dMiCE).
  • Employed Monte Carlo simulations to evaluate the algorithm's performance.

    • Main Results:

    • The statistical LOR estimator accurately determines 3D interaction points, even with multiple photon interactions.
    • The algorithm successfully estimates the first interaction point for coincidence photons.
    • Demonstrated significant improvement in LOR estimation accuracy compared to Anger logic across various parameters.
    • The dMiCE detector elements effectively provide DOI information.

    Conclusions:

    • The developed statistical LOR estimator offers a substantial advancement for high-resolution PET detector modules.
    • This method enhances image quality by improving the precision of interaction point localization.
    • The algorithm's ability to handle multiple interactions and provide DOI information makes it suitable for next-generation PET systems.