HR-pQCT

In contrast to a conventional computed tomography (CT) scanner, which provides contrast based on the attenuation of X-rays from different materials, High Resolution Peripheral Quantitative CT (HR-pQCT), determines the actual bone mineral density and can quantify the three-dimensional microarchitecture of the peripheral extremities with micrometer resolution. These insights can aid in diagnosing metabolic bone diseases, such as osteoporosis, and monitoring their progress and treatment.
However, this method's long acquisition time of approximately two minutes presents a major drawback, resulting in high susceptibility to patient motion and, thus, artifacts in the images produced.

This project aims to develop methods for automatically estimating motion artifact in a given image and compensating for them as needed. In this project, we collaborate with the department of osteology and biomechanics at UKE.

HR-pQCT image with severe motion artifacts.

Project Publications

[191982]
Title: Optimization-based motion estimation in HR-pQCT.
Written by: P. Jürß, T. Knopp, B. Busse, F.N. von Brackel, M. Boberg
in: <em>2025 IEEE International Symposium on Biomedical Imaging (ISBI)</em>. (2025).
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on pages: 1-4
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Note: inproceedings, hrpqct

Abstract: The imaging modality high-resolution peripheral quantitative computed tomography (HR-pQCT) enables assessment of bone mineral density and three-dimensional microarchitecture of peripheral limbs. Due to its long scan time, this modality is especially susceptible towards motion of the patient. The architecture and scanning protocol of existing scanners, which acquire only halfscans, make many existing methods of motion compensation inapplicable. In this work, an iterative motion estimation and compensation approach is proposed that is able to significantly reduce the amount of motion artifacts. This is achieved by jointly optimizing the motion parameters and reference image to minimize the data consistency error by exploiting the quasi-convex behavior of the objective functions observed near the ground truth. The proposed method was evaluated on a large collection of simulated sinograms and was able to remove motion artifacts almost completely.