# MR/PET Motion Correction from Coil Fingerprints

> **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2021 · $617,660

## Abstract

PROJECT SUMMARY:
This proposal is devoted to the development, clinical implementation and evaluation of a novel, real-time,
motion correction methodology for concurrent MR/PET acquisitions. Available methods for data acquisition and
reconstruction in MR/PET scanners do not fully capitalize on the simultaneous imaging capabilities of the
commercially available MR/PET instrumentation. These capabilities could be used to obtain real-time
information for reducing motion artifacts and partial voluming bias from PET images without significantly
affecting the workflow of the corresponding MRI examination. Our methodology builds on the track record of
the multi-institutional research team with all aspects of MRI and PET data acquisition and reconstruction. The
proposed methodology will lead to improved sensitivity and quantitative accuracy for PET scans when they are
simultaneously acquired during the course of an MR/PET examination. Such improvements will lead to better
detection, staging and surveillance of small (<1cm) abdominal lesions, which assessment is currently limited
due to excessive signal loss from motion blur and partial voluming bias.

## Key facts

- **NIH application ID:** 10158486
- **Project number:** 5R01EB029306-02
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Fernando E Boada
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $617,660
- **Award type:** 5
- **Project period:** 2020-05-04 → 2021-11-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10158486

## Citation

> US National Institutes of Health, RePORTER application 10158486, MR/PET Motion Correction from Coil Fingerprints (5R01EB029306-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10158486. Licensed CC0.

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