Jennifer Maier

All Publications

• Personalizing the shoulder rhythm in a computational upper body model improves kinematic tracking in high range-of-motion arm movements. Journal of biomechanics Maier, J. N., Bianco, N. A., Ong, C. F., Muccini, J., Kuhl, E., Delp, S. L. 2024; 176: 112365

  Abstract

  Musculoskeletal models of the shoulder are needed to understand the mechanics of overhead motions. Existing models implementing the shoulder rhythm are generic and might not accurately represent an individual's scapular kinematics. We introduce a method to personalize the shoulder rhythm of a computational model of the upper body that defines the orientations of the clavicle and scapula based on glenohumeral joint angles. During five static calibration poses, we palpate and measure the orientation of the scapula. We explore the importance of representing shoulder elevation by introducing clavicle elevation as a degree of freedom that is independent of the glenohumeral angles. For ten subjects, we record the five calibration poses, ten additional static poses, and dynamic arm raises covering the participants' full range of motion in each body plane using optical motion capture. We examine the data using a dynamically-constrained inverse kinematics analysis. Shoulder rhythm personalization, independent clavicle elevation, and both in combination reduce the average upper body marker tracking error compared to the generic model in the static poses (26 mm to 17-20 mm) and in the dynamic trials (22 mm to 14-17 mm). Only personalization reduces the average scapula marker error (51 mm to 36-38 mm) and scapula axis-angle error (15° to 10°) compared with the palpated ground truth measurements in the static poses, and in the dynamic trials at instances that best match the static poses (53 mm to 37-40 mm, 15° to 9°). Our results show that personalizing upper body models improves kinematic tracking. We provide our experimental data, model, and methods to allow researchers to reproduce and build upon our results.

  View details for DOI 10.1016/j.jbiomech.2024.112365

  View details for PubMedID 39426356

• Rigid and Non-rigid Motion Compensation in Weight-bearing CBCT of the Knee using Simulated Inertial Measurements. IEEE transactions on bio-medical engineering Maier, J., Nitschke, M., Choi, J. H., Gold, G., Fahrig, R., Eskofier, B. M., Maier, A. 2021; PP

  Abstract

  Involuntary subject motion is the main source of artifacts in weight-bearing cone-beam CT of the knee. To achieve image quality for clinical diagnosis, the motion needs to be compensated. We propose to use inertial measurement units (IMUs) attached to the leg for motion estimation.We perform a simulation study using real motion recorded with an optical tracking system. Three IMU-based correction approaches are evaluated, namely rigid motion correction, non-rigid 2D projection deformation and non-rigid 3D dynamic reconstruction. We present an initialization process based on the system geometry. With an IMU noise simulation, we investigate the applicability of the proposed methods in real applications.All proposed IMU-based approaches correct motion at least as good as a state-of-the-art marker-based approach. The structural similarity index and the root mean squared error between motion-free and motion corrected volumes are improved by 24-35% and 78-85%, respectively, compared with the uncorrected case. The noise analysis shows that the noise levels of commercially available IMUs need to be improved by a factor of 105 which is currently only achieved by specialized hardware not robust enough for the application.Our simulation study confirms the feasibility of this novel approach and defines improvements necessary for a real application.The presented work lays the foundation for IMU-based motion compensation in cone-beam CT of the knee and creates valuable insights for future developments.

  View details for DOI 10.1109/TBME.2021.3123673

  View details for PubMedID 34714730

• 3D Non-Rigid Alignment of Low-Dose Scans Allows to Correct for Saturation in Lower Extremity Cone-Beam CT IEEE ACCESS Maier, J., Maier, A., Eskofier, B., Fahrig, R., Choi, J. 2021; 9: 71821-71831

  Abstract

  Detector saturation in cone-beam computed tomography occurs when an object of highly varying shape and material composition is imaged using an automatic exposure control (AEC) system. When imaging a subject's knees, high beam energy ensures the visibility of internal structures but leads to overexposure in less dense border regions. In this work, we propose to use an additional low-dose scan to correct the saturation artifacts of AEC scans. Overexposed pixels are identified in the projection images of the AEC scan using histogram-based thresholding. The saturation-free pixels from the AEC scan are combined with the skin border pixels of the low-dose scan prior to volumetric reconstruction. To compensate for patient motion between the two scans, a 3D non-rigid alignment of the projection images in a backward-forward-projection process based on fiducial marker positions is proposed. On numerical simulations, the projection combination improved the structural similarity index measure from 0.883 to 0.999. Further evaluations were performed on two in vivo subject knee acquisitions, one without and one with motion between the AEC and low-dose scans. Saturation-free reference images were acquired using a beam attenuator. The proposed method could qualitatively restore the information of peripheral tissue structures. Applying the 3D non-rigid alignment made it possible to use the projection images with inter-scan subject motion for projection image combination. The increase in radiation exposure due to the additional low-dose scan was found to be negligibly low. The presented methods allow simple but effective correction of saturation artifacts.

  View details for DOI 10.1109/ACCESS.2021.3079368

  View details for Web of Science ID 000652048500001

  View details for PubMedID 34141516

  View details for PubMedCentralID PMC8208599

• Feasibility of Motion Compensation using Inertial Measurement in C-arm CT Maier, J., Aichert, A., Mehringer, W., Bier, B., Eskofier, B., Levenston, M., Gold, G., Fahrig, R., Bonaretti, S., Maier, A., IEEE IEEE. 2018

  View details for Web of Science ID 000601256000197

• Comparison of Different Approaches for Measuring Tibial Cartilage Thickness JOURNAL OF INTEGRATIVE BIOINFORMATICS Maier, J., Black, M., Bonaretti, S., Bier, B., Eskofier, B., Choi, J., Levenston, M., Gold, G., Fahrig, R., Maier, A. 2017; 14 (2)

  Abstract

  Osteoarthritis is a degenerative disease affecting bones and cartilage especially in the human knee. In this context, cartilage thickness is an indicator for knee cartilage health. Thickness measurements are performed on medical images acquired in-vivo. Currently, there is no standard method agreed upon that defines a distance measure in articular cartilage. In this work, we present a comparison of different methods commonly used in literature. These methods are based on nearest neighbors, surface normal vectors, local thickness and potential field lines. All approaches were applied to manual segmentations of tibia and lateral and medial tibial cartilage performed by experienced raters. The underlying data were contrast agent-enhanced cone-beam C-arm CT reconstructions of one healthy subject's knee. The subject was scanned three times, once in supine position and two times in a standing weight-bearing position. A comparison of the resulting thickness maps shows similar distributions and high correlation coefficients between the approaches above 0.90. The nearest neighbor method results on average in the lowest cartilage thickness values, while the local thickness approach assigns the highest values. We showed that the different methods agree in their thickness distribution. The results will be used for a future evaluation of cartilage change under weight-bearing conditions.

  View details for DOI 10.1515/jib-2017-0015

  View details for Web of Science ID 000406931200005

  View details for PubMedID 28753537

• Object Removal in Gradient Domain of Cone-Beam CT Projections Bier, B., Berger, M., Maier, J., Unberath, M., Hsieh, S., Bonaretti, S., Fahrig, R., Levenston, M. E., Gold, G. E., Maier, A., IEEE IEEE. 2016

  View details for Web of Science ID 000432419500102

• Analog Non-Linear Transformation-Based Tone Mapping for Image Enhancement in C-arm CT Shi, L., Berger, M., Bier, B., Soell, C., Roeber, J., Fahrig, R., Eskofier, B., Maier, A., Maier, J., IEEE IEEE. 2016

  View details for Web of Science ID 000432419500112