@incollection{Strobel, author = {Strobel, Norbert}, title = {Fusion of Multisensor Data}, series = {Principles of 3D Image Analysis and Synthesis}, booktitle = {Principles of 3D Image Analysis and Synthesis}, editor = {Girod, B. and Greiner, G. and Niemann, H.}, publisher = {Kluwer Academic Publishers}, address = {Boston, USA}, pages = {309 -- 322}, language = {en} } @incollection{StrobelRabenstein, author = {Strobel, Norbert and Rabenstein, Rudolf}, title = {Object Localization using Audio and Video Signals}, series = {Principles of 3D Image Analysis and Synthesis}, booktitle = {Principles of 3D Image Analysis and Synthesis}, editor = {Girod, G. and Greiner, G. and Niemann, H.}, publisher = {Kluwer Academic Publishers}, address = {Boston, USA}, pages = {322 -- 334}, language = {en} } @phdthesis{StrobelMitra, author = {Strobel, Norbert and Mitra, Sanjit K.}, title = {Multiresolution-based storage, browsing and retrieval for digital image libraries}, publisher = {Department of Electrical and Computer Engineering, Signal and Image Processing Laboratory}, address = {Santa Barbara, USA}, abstract = {In this dissertation, the focus is on algorithms for progressive-resolution image transmission, storage and retrieval. The resulting methods are designed to support a fast system response, to provide an intuitive image representation, and to achieve lossless image compression at competitive bit rates. Average interpolation subdivision (AIS) is introduced. It offers a sound mathematical framework for the derivation of algorithms providing the functionality required. To proceed from AIS to image compression, a multiresolution analysis is added. It allows the construction of wavelet transforms and leads to AIS filter banks. For lossless image compression, reversible wavelet transforms (RWTs) are constructed. To that end, an interband prediction structure for AIS filter banks is first derived. Afterwards rounding operations are introduced, and RWTs are assembled. Reversible AIS filter banks deliver acceptable bit rates when applied to the lossless compression of monochrome images. A time-domain filter analysis confirms that AIS filters are nearly optimal given their structural constraints. Better results are still obtainable. They, however, require an enhanced interband prediction framework. If images of arbitrary size are to be ingested into a database, an efficient method is needed to process signal boundaries. It is demonstrated that interband-prediction offers an elegant and practical solution for this task. The reversible AIS filter banks are finally applied to the lossless compression of color images. Color images offer an excellent opportunity for the design of algorithms which are applicable to a much wider range of multispectral imagery. A new lossless compression method is proposed. It executes a reversible wavelet transform first and then applies adaptive spectral transforms to associated color subbands. Very good results have been obtained. Yet, little computational complexity has been added. Simulation results are included. They verify the rationale of this approach.}, language = {en} } @article{KochHoffmannPfisteretal., author = {Koch, Martin and Hoffmann, Matthias and Pfister, Marcus and Hornegger, Joachim and Strobel, Norbert}, title = {Optimized viewing angles for cardiac electrophysiology ablation procedures}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {10}, journal = {International Journal of Computer Assisted Radiology and Surgery}, publisher = {Springer}, doi = {10.1007/s11548-014-1103-z}, pages = {651 -- 664}, abstract = {Purpose: Catheter ablation is a common treatment option for atrial fibrillation (AF). Interventional C-arm X-ray systems are used for guiding AF procedures, employing standard view positions. Since the projection angles are not adapted to the individual patient anatomy, standard projections do not necessarily offer the best views of important anatomical structures. Using a pre-procedural 3D data set acquired with MRI or CT, suitable ablation sites (lines) can be identified in advance so an ablation plan can be superimposed on fluoroscopic images to guide the procedure. Methods: A method was developed to estimate optimized projection views for biplane X-ray C-arm systems based on planning data for AF ablation procedures. The estimated viewing angles were compared to standard angulations using an objective quality metric, the length of the planned ablation line as seen under X-ray. This method was tested using 35 clinical datasets annotated with planned ablation lines for ipsilateral pulmonary vein isolation. Results: The optimized views computed using the new method yielded 28 \% less foreshortening of pre-planned ablation lines on average. In one case, anatomy-based view calculation lead to a 69 \% reduction in foreshortening. Conclusion: The commonly used standard views provide reasonable a priori choices, and some improvement is possible by switching among common angulations depending on the treatment region. Further gains are possible by using anatomy-optimized biplane C-arm angulations.}, language = {en} } @article{KurzendorferGirardGralewskietal., author = {Kurzendorfer, Tanja and Girard, Erin and Gralewski, Kevin and Kleinoeder, Andreas and Kiraly, Atilla P and Strobel, Norbert and Dori, Yoav}, title = {New biplane x-ray magnetic resonance image fusion prototype for 3D enhanced cardiac catheterization in congenital heart diseases}, series = {Journal of Cardiovascular Magnetic Resonance}, volume = {16}, journal = {Journal of Cardiovascular Magnetic Resonance}, number = {Supplement 1}, doi = {10.1186/1532-429X-16-S1-O103}, abstract = {Background X-ray magnetic resonance fusion (XMRF) is used to enhance fluoroscopically guided catheterization procedures. We present a new method for biplane XMRF involving an augmented fluoroscopy prototype (Siemens, Forchheim, Germany). With this software it is possible to register 3D MRI data to biplane X-ray projections based on internal markers, without the need for a C-arm CT to perform 3D/3D registration. The software supports overlaying volume rendered data as well as multiple surface models. Visualization techniques, such as contour or solid rendering and surface carving are supported to allow for clear presentation of complex 3D structures. Methods We reviewed data obtained with different visualization methods on 20 patients that underwent clinical XMRF procedures. Surface models were generated by threshold based segmentation from high resolution MRA (syngo Twist or Navigator gated 3D flash IR sequence) of structures of interest using Mimics (Leuven, Belgium). Initial registration was achieved through planar alignment of the volume in anterior-posterior (AP) and lateral projections matching anatomical landmarks, such as the heart and vessel borders. In addition, the registration accuracy of the prototype was assessed using a phantom by measuring the maximum distance between a single point and the 3D model boundaries in comparison to the boundaries seen on fluoroscopy. Results The maximum segmentation time was 10 min and the initial registration required less than 30 sec. Registration was performed without the need for contrast injection or additional radiation exposure. The registration error based on phantom measurements was 2.2 ± 1.1 mm in the AP projection and 1.36 ± 0.7 mm in the lateral projection. For surface rendered data, solid rendering with carving provided the optimal display of complex 3D data. In contrast to volume rendering, solid surface rendering provides delineation of the 3D relation between objects and clear visualization of internal structures such as ostia of the vessels and muscle bundles using the carving feature, see Figure 1. Contour rendering offered reasonable visualization for smooth, uncomplicated structures like the atria, but it was not ideal for complex overlapping structures due to missing 3D depth information. When multiple surfaces are loaded, contour rendering was, however, found to be useful in combination with solid rendered structures to provide a see-through 3D relation between multiple structures Conclusions The prototype demonstrated a high level of accuracy for fluoroscopic overlays. Biplane internal marker based registration can be performed quickly, without the need for additional radiation or contrast. We found solid rendering of surface models in combination with carving techniques to be most useful for visualization. This new biplane XMRF technique has the potential to provide enhanced guidance under fluoroscopy by integrating 3D information and to reduce radiation during complicated catheterization procedures. Funding This project is funded by a research grant from Siemens, AG, Healthcare, Forchheim, Germany. The concepts and information presented in this paper are based on research and are not commercially available.}, language = {en} } @article{KochBrostBourieretal., author = {Koch, Martin W. and Brost, Alexander and Bourier, Felix and Hornegger, Joachim and Strobel, Norbert}, title = {Automatic planning of atrial fibrillation ablation lines using landmark-constrained nonrigid registration}, series = {Journal of Medical Imaging}, volume = {1}, journal = {Journal of Medical Imaging}, number = {1}, doi = {10.1117/1.JMI.1.1.015002}, abstract = {Catheter ablation is a common treatment option for drug-refractory atrial fibrillation. In many cases, pulmonary vein isolation is the treatment of choice. With current fluoro overlay methods or electroanatomic mapping systems, it is possible to visualize three-dimensional (3-D) anatomy as well as target ablation lines to provide additional context information. Today, however, these lines need to be set manually before the procedure by the physician, which may interrupt the clinical workflow. As a solution, we present an automatic approach for the planning of ablation target lines. Our method works on surface models extracted from 3-D images. To propose suitable ablation lines, a reference model annotated with reference ablation lines is nonrigidly registered to the model segmented from a new patient's 3-D data. After registration, the reference plan is transferred from the reference anatomy to the individual patient anatomy. Due to the high anatomical variations observed in clinical practice, additional landmark constraints are employed in the registration process to increase the robustness of our approach. We evaluated our method on 43 clinical datasets by benchmarking it against professionally planned ablation lines and achieved an average error over all datasets of 2.7±2.0  mm . A qualitative evaluation of the ablation planning lines matched clinical expectations.}, language = {en} } @misc{WuChenStrobeletal., author = {Wu, W. and Chen, T. and Strobel, Norbert and Comaniciu, D.}, title = {Method and system for ablation catheter and circumferential mapping catheter tracking in fluoroscopic images (Patent, US 9,002,436)}, language = {en} } @misc{BarbotKiralyStrobel, author = {Barbot, Julien Christian and Kiraly, Atilla Peter and Strobel, Norbert}, title = {Localization and tracking of cryo-balloon during interventional fluoroscopy imaging (Patent, US 8989463B2)}, abstract = {A method for the detection of a balloon catheter within a fluoroscopic image, including: removing noise from a fluoroscopic image; detecting edges of a balloon catheter in the fluoroscopic image, wherein the detected edges include subsets of connected edges; extracting an edge subset from the subsets of connected edges; fitting a model to the extracted edge subset; removing outliers of the extracted edge subset based on the fitting of the model; adding the extracted edge subset without the outlier to a data set; repeating the extracting, fitting, removing and adding steps for the remainder of the subsets of connected edges; and fitting the model to the data set, wherein the data set is indicative of the balloon catheter.}, language = {en} } @misc{SchoenBlohmDannenmannetal., author = {Sch{\"o}n, N. and Blohm, L. and Dannenmann, T. and Dennerlein, F. and Hoheisel, M. and Strobel, Norbert}, title = {Verfahren zur Registrierung eines ersten Koordinatensystems einer ersten medizinischen Bildgebungseinrichtung mit einem zweiten Koordinatensystemeiner zweitenmedizinischen Bildgebungseinrichtung und/oder einem dritten Koordinatensystem eines medizinischen Instruments, welches durchMarker einer medizinischen Navigationseinrichtung definiert ist, und medizinisches Untersuchungs- und/oder Behandlungssystem (Patent, DE 102011006537)}, language = {de} } @misc{DennerleinBlohmVogtetal., author = {Dennerlein, F. and Blohm, L. and Vogt, M. and Hoheisel, M. and Sch{\"o}n, N. and Strobel, Norbert and Dannenmann, T.}, title = {Verfahren und System zur Unterst{\"u}tzung des Arbeitsablaufs in einer Operationsumgebung (Patent, DE102011006574)}, language = {de} } @inproceedings{HariharanKaethnerStrobeletal., author = {Hariharan, Sai Gokul and Kaethner, Christian and Strobel, Norbert and Kowarschik, Markus and Albarqouni, Shadi and Fahrig, Rebecca and Navab, Nassir}, title = {Learning-based X-ray image denoising utilizing model-based image simulations}, series = {International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2019, 22nd International Conference Shenzhen, China, October 13-17, 2019 Proceedings, Part VI}, booktitle = {International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2019, 22nd International Conference Shenzhen, China, October 13-17, 2019 Proceedings, Part VI}, publisher = {Springer International Publishing}, address = {Cham}, doi = {10.1007/978-3-030-32226-7_61}, pages = {549 -- 557}, language = {en} } @inproceedings{HariharanKaethnerStrobeletal., author = {Hariharan, Sai Gokul and Kaethner, Christian and Strobel, Norbert and Kowarschik, Markus and DiNitto, Julie and Fahrig, Rebecca and Navab, Nassir}, title = {Model-based motion artifact correction in digital subtraction angiography using optical-flow}, series = {Bildverarbeitung f{\"u}r die Medizin 2019: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 17. bis 19. M{\"a}rz 2019 in L{\"u}beck}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 17. bis 19. M{\"a}rz 2019 in L{\"u}beck}, publisher = {Springer Fachmedien}, address = {Wiesbaden}, doi = {10.1007/978-3-658-25326-4_31}, pages = {146 -- 151}, language = {en} } @inproceedings{SpiessFriesslichBluemmetal., author = {Spieß, Florian and Friesslich, Jonas and Bluemm, Daniel and Mast, Fabio and Vinokour, Dmitrij and Kounev, Samuel and Kaupp, Tobias and Strobel, Norbert}, title = {Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment}, series = {2021 20th International Conference on Advanced Robotics (ICAR)}, booktitle = {2021 20th International Conference on Advanced Robotics (ICAR)}, doi = {10.1109/ICAR53236.2021.9659355}, pages = {857 -- 864}, abstract = {To arrive at a realistic assessment of localization methods in terms of their performance in an industrial environment under various challenging conditions, we provide a benchmark to evaluate algorithms both for individual components as well as multi-sensor systems. For several sensor types, including wheel odometry, RGB cameras, RGB-D cameras, and LIDAR, potential issues were identified. The accuracy of wheel odometry, for example, when there are bumps on the track. For each sensor type, we explicitly chose a track for the benchmark dataset containing situations where the sensor fails to provide adequate measurements. Based on the acquired sensor data, localization can be achieved either using a single sensor information or sensor fusion. To help evaluate the output of associated localization algorithms, we provide a software to evaluate a set of metrics as part of the paper. An example application of the benchmark with state-of-the-art algorithms for each sensor is also provided.}, language = {en} } @article{SpiessReinhartStrobeletal., author = {Spiess, Florian and Reinhart, Lukas and Strobel, Norbert and Kaupp, Tobias and Kaiser, Dennis and Kounev, Samuel}, title = {People detection with depth silhouettes and convolutional neural networks on a mobile robot}, series = {Journal of Image and Graphics}, volume = {9}, journal = {Journal of Image and Graphics}, number = {4}, pages = {135 -- 139}, abstract = {This paper presents a novel people detection approach for mobile robot applications based on a combination of classical computer vision techniques and a state-of-the-art neural network. Our approach involves an RGB-D camera as an environmental sensor. The depth data is used to extract silhouettes around people. The RGB images are subsequently augmented with this border information before passing it to the neural network. Under challenging lighting conditions, our system was able to outperform the neural network trained on regular RGB data alone by a factor of two.}, language = {en} } @inproceedings{SpiessStrobelKauppetal., author = {Spiess, Florian and Strobel, Norbert and Kaupp, Tobias and Kounev, Samuel}, title = {A data-driven Sensor Model for LIDAR Range Measurements used for Mobile Robot Navigation}, series = {2022 Sixth IEEE International Conference on Robotic Computing (IRC)}, booktitle = {2022 Sixth IEEE International Conference on Robotic Computing (IRC)}, doi = {10.1109/IRC55401.2022.00020}, pages = {76 -- 80}, abstract = {In this paper, an analysis of the precision of LIDAR range measurements is presented. LIDAR data from two different sensors (HLS-LFCD-LDS and SICK TIM561) were analyzed regarding the influence of range, incident angle to the surface, and material. Based on the results, a data-driven model for LIDAR precision behavior was developed, and a comparison with standard deviation models based on the vendor-provided specifications was presented. Our model can be used to create realistic sensor simulations and to develop robot navigation algorithms weighing sensor range readings based on the precision.}, language = {en} } @article{SpiessFriesslichKauppetal., author = {Spiess, Florian and Friesslich, Jonas and Kaupp, Tobias and Kounev, Samuel and Strobel, Norbert}, title = {Survey and Experimental Comparison of RGB-D Indoor Robot Navigation Methods Supported by ROS and Their Expansion via Fusion with Wheel Odometry and IMU Data}, series = {International Journal of Mechanical Engineering and Robotics Research}, volume = {9}, journal = {International Journal of Mechanical Engineering and Robotics Research}, number = {12}, doi = {10.18178/ijmerr.9.12.1532-1540}, pages = {1532 -- 1540}, language = {en} } @article{SpiessStrobelKauppetal., author = {Spiess, Florian and Strobel, Norbert and Kaupp, Tobias and Kounev, Samuel}, title = {A data-driven Model for Range Sensors}, series = {Encyclopedia with Semantic Computing and Robotic Intelligence}, journal = {Encyclopedia with Semantic Computing and Robotic Intelligence}, language = {en} } @inproceedings{RoserZhongBirkholdetal., author = {Roser, Philipp and Zhong, Xia and Birkhold, Annette and Preuhs, Alexander and Syben, Christopher and Hoppe, Elisabeth and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Simultaneous estimation of X-ray back-scatter and forward-scatter using multi-task learning}, series = {Medical Image Computing and Computer Assisted Intervention-MICCAI 2020: 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II 23}, booktitle = {Medical Image Computing and Computer Assisted Intervention-MICCAI 2020: 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II 23}, publisher = {Springer International Publishing}, doi = {10.1007/978-3-030-59713-9_20}, pages = {199 -- 208}, language = {en} } @inproceedings{ZhongRoserBayeretal., author = {Zhong, Xia and Roser, Philipp and Bayer, Siming and Ravikumar, Nishant and Strobel, Norbert and Birkhold, Annette and Horz, Tim and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Pediatric Patient Surface Model Atlas Generation and X-Ray Skin Dose Estimation}, series = {Bildverarbeitung f{\"u}r die Medizin 2019: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 17. bis 19. M{\"a}rz 2019 in L{\"u}beck}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 17. bis 19. M{\"a}rz 2019 in L{\"u}beck}, publisher = {Springer Fachmedien}, address = {Wiesbaden}, doi = {10.1007/978-3-658-25326-4_27}, pages = {122 -- 127}, language = {en} } @inproceedings{RoserBirkholdPreuhsetal., author = {Roser, Philipp and Birkhold, Annette and Preuhs, Alexander and Syben, Christopher and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Deep scatter splines: Learning-based medical X-ray scatter estimation using B-splines}, series = {The 6th International Conference on Image Formation in X-Ray Computed Tompgraphy}, booktitle = {The 6th International Conference on Image Formation in X-Ray Computed Tompgraphy}, language = {en} } @inproceedings{ShettyBirkholdStrobeletal., author = {Shetty, Karthik and Birkhold, Annette and Strobel, Norbert and Egger, Bernhard and Jaganathan, Srikrishna and Kowarschik, Markus and Maier, Andreas}, title = {Deep Learning Compatible Differentiable X-ray Projections for Inverse Rendering}, series = {Bildverarbeitung f{\"u}r die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2021: Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9}, publisher = {Springer Fachmedien}, address = {Wiesbaden}, pages = {290 -- 295}, language = {en} } @inproceedings{ShettyBirkholdJaganathanetal., author = {Shetty, Karthik and Birkhold, Annette and Jaganathan, Srikrishna and Strobel, Norbert and Kowarschik, Markus and Maier, Andreas and Egger, Bernhard}, title = {PLIKS - A Pseudo-Linear Inverse Kinematic Solver for3D Human Body Estimation}, series = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages = {574 -- 584}, language = {en} } @article{HariharanKaethnerStrobeletal., author = {Hariharan, Sai Gokul and Kaethner, Christian and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Navab, Nassir}, title = {Robust learning-based x-ray image denoising—potential pitfalls, their analysis and solutions}, series = {Biomedical Physics \& Engineering Express}, volume = {8}, journal = {Biomedical Physics \& Engineering Express}, number = {3}, doi = {10.1088/2057-1976/ac3489}, language = {en} } @article{MaulRoserBirkholdetal., author = {Maul, Noah and Roser, Philipp and Birkhold, Annette and Kowarschik, Markus and Zhong, Xia and Strobel, Norbert and Maier, Andreas}, title = {Learning-based occupational x-ray scatter estimation}, series = {Physics in Medicine and Biology}, volume = {67}, journal = {Physics in Medicine and Biology}, number = {7}, doi = {10.1088/1361-6560/ac58dc}, language = {en} } @article{ZhongAmrehnRavikumaretal., author = {Zhong, Xia and Amrehn, Mario and Ravikumar, Nishant and Chen, Shuqing and Strobel, Norbert and Birkhold, Annette and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Deep action learning enables robust 3D segmentation of body organs in various CT and MRI images}, series = {Scientific Reports}, volume = {11}, journal = {Scientific Reports}, number = {1}, doi = {10.1038/s41598-021-82370-6}, language = {en} } @article{RoserBirkholdPreuhsetal., author = {Roser, Philipp and Birkhold, Annette and Preuhs, Alexander and Stimpel, Bernhard and Syben, Christopher and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {Fully-automatic CT data preparation for interventional X-ray skin dose simulation}, series = {Bildverarbeitung f{\"u}r die Medizin 2020: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2020 in Berlin}, journal = {Bildverarbeitung f{\"u}r die Medizin 2020: Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 15. bis 17. M{\"a}rz 2020 in Berlin}, publisher = {Springer Fachmedien}, address = {Wiesbaden}, doi = {10.1007/978-3-658-29267-6_26}, pages = {125 -- 130}, language = {en} } @article{BuschStrobelNobachetal., author = {Busch, Erik and Strobel, Norbert and Nobach, Kai and Bulitta, Clemens and Hirshfeld, John W. and Lin, Wu and de Abreu, Marcel Gama}, title = {Optimizing the innovation and development process of medical devices - a study based on angiographic equipment}, series = {Health and Technology}, volume = {11}, journal = {Health and Technology}, number = {3}, doi = {doi.org/10.1007/s12553-021-00537-7}, pages = {563 -- 574}, language = {en} } @article{RoserBirkholdPreuhsetal., author = {Roser, Philipp and Birkhold, Annette and Preuhs, Alexander and Ochs, Philipp and Stepina, Elizaveta and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {XDose: toward online cross-validation of experimental and computational X-ray dose estimation}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {16}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {2}, doi = {10.1007/s11548-020-02298-6}, language = {en} } @article{RoserBirkholdPreuhsetal., author = {Roser, Philipp and Birkhold, Annette and Preuhs, Alexander and Syben, Christopher and Felsner, Lina and Hoppe, Elisabeth and Strobel, Norbert and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {X-ray Scatter Estimation Using Deep Splines}, series = {IEEE Transactions on Medical Imaging}, volume = {40}, journal = {IEEE Transactions on Medical Imaging}, number = {9}, pages = {2272 -- 2283}, language = {en} } @article{HariharanStrobelKaethneretal., author = {Hariharan, Sai Gokul and Strobel, Norbert and Kaethner, Christian and Kowarschik, Markus and Fahrig, Rebecca and Navab, Nassir}, title = {Data-driven estimation of noise variance stabilization parameters for low-dose x-ray images}, series = {Physics in Medicine and Biology}, volume = {65}, journal = {Physics in Medicine and Biology}, number = {22}, doi = {10.1088/1361-6560/abbc82}, language = {en} } @article{ZhongStrobelBirkholdetal., author = {Zhong, Xia and Strobel, Norbert and Birkhold, Annette and Kowarschik, Markus and Fahrig, Rebecca and Maier, Andreas}, title = {A machine learning pipeline for internal anatomical landmark embedding based on a patient surface model}, series = {International Journal of Computer Assisted Radiology and Surgery}, volume = {14}, journal = {International Journal of Computer Assisted Radiology and Surgery}, number = {1}, doi = {10.1007/s11548-018-1871-y}, pages = {53 -- 61}, language = {en} } @article{ShettyBirkholdJaganathanetal., author = {Shetty, Karthik and Birkhold, Annette and Jaganathan, Srikrishna and Strobel, Norbert and Egger, Bernhard and Kowarschik, Markus and Maier, Andreas}, title = {BOSS: Bones, organs and skin shape model}, series = {Computers in Biology and Medicine}, volume = {165}, journal = {Computers in Biology and Medicine}, issn = {0010-4825}, language = {en} }