Jennifer Maier
Dr.-Ing. Jennifer Maier
Since 05/2017 | Researcher and Ph.D. student in the Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg |
Since 01/2016 | Researcher and Ph.D. student in the Medical Image Reconstruction Group, Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg |
05/2015 – 10/2015 | Master thesis: Research stay at the Laboratory of Movement Analysis and Measurement, École polytechnique fédérale de Lausanne |
10/2013 – 12/2015 | M.Sc. in Medical Engineering at the Friedrich-Alexander-Universität Erlangen-Nürnberg |
10/2010 – 03/2014 | B. Sc in Medical Engineering at the Friedrich-Alexander-Universität Erlangen-Nürnberg |
09/2001 – 06/2010 | Secondary school at Gymnasium Naila |
2022
Rigid and Non-Rigid Motion Compensation in Weight-Bearing CBCT of the Knee Using Simulated Inertial Measurements
In: IEEE Transactions on Biomedical Engineering 69 (2022), p. 1608-1619
ISSN: 0018-9294
DOI: 10.1109/TBME.2021.3123673
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2021
Methods for Weight-bearing C-arm Cone-Beam Computed Tomography of the Knees (Dissertation, 2021)
URL: https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/17559
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3D Non-Rigid Alignment of Low-Dose Scans Allows to Correct for Saturation in Lower Extremity Cone-Beam CT
In: IEEE Access 9 (2021), p. 71821-71831
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3079368
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Inertial Measurements for Motion Compensation in Weight-bearing Cone-beam CT of the Knee
German Workshop on Medical Image Computing, 2021 (Regensburg, 7. March 2021 - 9. March 2021)
In: Christoph Palm, Heinz Handels, Klaus Maier-Hein, Thomas M. Deserno, Andreas Maier, Thomas Tolxdorff (ed.): Informatik aktuell 2021
DOI: 10.1007/978-3-658-33198-6_81
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Analysis of Interventional Workflow Phases based on Image Classification
65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) (Berlin (online conference), 6. September 2020 - 9. September 2020)
In: 65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) 2021
DOI: 10.3205/20gmds187
URL: https://www.egms.de/static/en/meetings/gmds2020/20gmds187.shtml
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EXACT: a collaboration toolset for algorithm-aided annotation of images with annotation version control
In: Scientific Reports 11 (2021), Article No.: 4343
ISSN: 2045-2322
DOI: 10.1038/s41598-021-83827-4
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2020
Inertial Measurements for Motion Compensation in Weight-Bearing Cone-Beam CT of the Knee
In: Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz (ed.): Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, 2020, p. 14-23
ISBN: 9783030597153
DOI: 10.1007/978-3-030-59716-0_2
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Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT
In: Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (ed.): Bildverarbeitung für die Medizin 2020, Wiesbaden: Springer Vieweg, 2020, p. 67-72 (Informatik aktuell)
ISBN: 9783658292669
DOI: 10.1007/978-3-658-29267-6_14
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Is crowd-algorithm collaboration an advanced alternative to crowd-sourcing on cytology slides?
International workshop on Algorithmen - Systeme - Anwendungen, 2020 (Berlin, 15. March 2020 - 17. March 2020)
In: Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (ed.): Informatik aktuell 2020
DOI: 10.1007/978-3-658-29267-6_5
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2019
Isocenter Determination from Projection Matrices of a C-Arm CBCT
Workshop on Bildverarbeitung fur die Medizin, 2019 (Lübeck, 17. March 2019 - 19. March 2019)
In: Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (ed.): Informatik aktuell 2019
DOI: 10.1007/978-3-658-25326-4_61
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Smooth Ride: Low-Pass Filtering of Manual Segmentations Improves Consensus
Bildverarbeitung für die Medizin 2019 (Lübeck, 17. March 2019 - 19. March 2019)
In: Bildverarbeitung für die Medizin 2019 2019
DOI: 10.1007/978-3-658-25326-4_21
URL: https://link.springer.com/chapter/10.1007/978-3-658-25326-4_21
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Automatic orientation estimation of inertial sensors in C-Arm CT Projections
In: Current Directions in Biomedical Engineering 5 (2019), p. 195-198
ISSN: 2364-5504
DOI: 10.1515/cdbme-2019-0050
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2018
Feasibility of Motion Compensation using Inertial Measurement in C-arm CT
2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (Sydney, 10. November 2018 - 17. November 2018)
In: Conference Record of the 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) 2018
DOI: 10.1109/nssmic.2018.8824463
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2017
Motion Compensation using Range Imaging in C-arm Cone-Beam CT
Medical Image Understanding and Analysis (21st Annual Conference, MIUA 2017) (Edinburgh, 11. July 2017 - 13. July 2017)
In: Medical Image Understanding and Analysis 2017
DOI: 10.1007/978-3-319-60964-5_49
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Bier17-MCU.pdf
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Surface Registration to Estimate Motion in CBCT
IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (Atlanta, 21. October 2017 - 28. October 2017)
In: 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC) 2017
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Bier17-SRT.pdf
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Comparison of Different Approaches for Measuring Tibial Cartilage Thickness
In: Journal of integrative bioinformatics 14 (2017)
ISSN: 1613-4516
DOI: 10.1515/jib-2017-0015
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Simultaneous Generation of X-ray and Range Images using XCAT under Motion
2017 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC) (Atlanta, Georgia, 21. October 2017 - 28. November 2017)
Open Access: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Rybakov17-SGO.pdf
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Rybakov17-SGO.pdf
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2016
Object Removal in Gradient Domain of Cone-Beam CT Projections
IEEE Nuclear Science Symposuim & Medical Imaging Conference (NSS/MIC) (Straßburg, 29. October 2016 - 5. November 2016)
In: 2016 IEEE Nuclear Science Symposuim & Medical Imaging Conference Record 2016
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Bier16-ORI.pdf
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Analog Non-Linear Transformation-Based Tone Mapping for Image Enhancement in C-arm CT
IEEE Medical Imaging Conference (MIC) (Strasbourg, France)
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2013
Automatic detection of inertial sensor orientation for movement analysis in Parkinsons disease
BSA Conference 2013 - Biosignal Analysis (Rio de Janeiro, Brazil)
In: BSA Conference 2013 - Biosignal Analysis 2013
URL: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2013/Maier13-ADO.pdf
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My PhD project focuses on the correction of involuntary motion during C-arm CT scans using biomechanical modeling.
2019
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PPP Brasilien 2019
(Third Party Funds Single)
Term: 1. January 2019 - 31. December 2020
Funding source: Deutscher Akademischer Austauschdienst (DAAD)
2018
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Automatic Intraoperative Tracking for Workflow and Dose Monitoring in X-Ray-based Minimally Invasive Surgeries
(Third Party Funds Single)
Term: 1. June 2018 - 31. May 2021
Funding source: Bundesministerium für Bildung und Forschung (BMBF)The goal of this project is the investigation of multimodal methods for the evaluation of interventional workflows in the operation room. This topic will be researched in an international project context with partners in Germany and in Brazil (UNISINOS in Porto Alegre). Methods will be developed to analyze the processes in an OR based on signals from body-worn sensors, cameras and other modalities like X-ray images recorded during the surgeries. For data analysis, techniques from the field of computer vision, machine learning and pattern recognition will be applied. The system will be integrated in a way that body-worn sensors developed by Portabiles as well as angiography systems produced by Siemens Healthcare can be included alongside.
2012
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RTG 1773: Heterogeneous Image Systems, Project C1
(Third Party Funds Group – Sub project)
Overall project: GRK 1773: Heterogene Bildsysteme
Term: 1. October 2012 - 31. March 2017
Funding source: DFG / Graduiertenkolleg (GRK)Especially in aging populations, Osteoarthritis (OA) is one of the leading causes for disability and functional decline of the body. Yet, the causes and progression of OA, particularly in the early stages, remain poorly understood. Current OA imaging measures require long scan times and are logistically challenging. Furthermore they are often insensitive to early changes of the tissue.The overarching goal of this project is the development of a novel computed tomography imaging system allowing for an analysis of the knee cartilage and menisci under weight-bearing conditions. The articular cartilage deformation under different weight-bearing conditions reveals information about abnormal motion patterns, which can be an early indicator for arthritis. This can help to detect the medical condition at an early stage.
To allow for a scan in standing or squatting position, we opted for a C-arm CT device that can be almost arbitrarily positioned in space. The standard application area for C-arm CT is in the interventional suite, where it usually acquires images using a vertical trajectory around the patient. For the recording of the knees in this project, a horizontal trajectory has been developed.
Scanning in standing or squatting position makes an analysis of the knee joint under weight-bearing conditions possible. However, it will also lead to involuntary motion of the knees during the scan. The motion will result in artifacts in the reconstruction that reduce the diagnostic image quality. Therefore, the goal of this project is to estimate the patient motion during the scan to reduce these artifacts. One approach is to compute the motion field of the knee using surface cameras and use the result for motion correction. Another possible approach is the design and evaluation of a biomechanical model of the knee using inertial sensors to compensate for movement.
After the correction of the motion artifacts, the reconstructed volume is used for the segmentation and quantitative analysis of the knee joint tissue. This will give information about the risk or the progression of an arthrosis disease.