# Wave-Cam: A novel micro-radar imaging array for non-rigid motion estimation in hybrid medical imaging

> **NIH NIH R21** · UNIV OF MASSACHUSETTS MED SCH WORCESTER · 2021 · $163,978

## Abstract

Abstract
 During medical imaging, patient motion is unavoidable and can result in significant image degradation. Heart
disease and cancer account for almost half of all deaths in the U.S. and considering the prevalence of imaging
for diagnosis, therapeutic monitoring, and surgical planning for these diseases, degraded images due to patient
motion can have significant implications. Furthermore, in multi-modal imaging the potential for misalignment from
patient motion between sequential acquisitions distorts intermodality alignment decreasing the utility of imaging.
Existing strategies for motion correction are classified as either: 1) data-driven by utilizing imaging data or 2) use
of a device external to the imaging system(s) that estimates motion of internal volumes of interest (VOI) by
tracking the motion of a surrogate, such as the patient’s body surface. External motion tracking (EMT) is a
popular alternative to data-driven approaches as it is unaffected by modality characteristics, such noise levels
and radiotracer distribution and can be used for tracking in multi-modal systems. The majority of EMT cameras
actively illuminate patients with visible or near infrared electromagnetic radiation that is reflected back by patient
garments. The opaqueness of garments to this type of radiation prevents tracking of the patient’s actual body
surface, thereby adding a level of uncertainty when estimating the motion. Thus, if the patient is clothed, then
current EMTs only track garments or markers which are themselves acting as surrogates to the patient’s body
surface, which is tantamount to tracking a surrogate to another surrogate to the VOI. Our premise is that patient
garments pose an unsurmountable barrier to EMTs that limit their motion tracking and compensation
performance in clinical imaging. As such, we propose to develop a novel EMT that utilizes a part of the
electromagnetic spectrum for which clothing is transparent, thus overcoming this limitation, and in turn
transforming the way motion tracking is performed in clinical settings.

## Key facts

- **NIH application ID:** 10022314
- **Project number:** 5R21EB027250-02
- **Recipient organization:** UNIV OF MASSACHUSETTS MED SCH WORCESTER
- **Principal Investigator:** Clifford Lindsay
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $163,978
- **Award type:** 5
- **Project period:** 2019-09-21 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10022314

## Citation

> US National Institutes of Health, RePORTER application 10022314, Wave-Cam: A novel micro-radar imaging array for non-rigid motion estimation in hybrid medical imaging (5R21EB027250-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10022314. Licensed CC0.

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