Dr. Stefan Heldmann - Fraunhofer MEVIS

Publications

2020

Borovec J, Kybic J, Arganda-Carreras I, Sorokin DV, Bueno G, Khvostikov AV, Bakas S, I-Chao Chang E, Heldmann S, Kartasalo K, Latonen L, Lotz J, Noga M, Pati S, Punithakumar K, Ruusuvuori P, Skalski A, Tahmasebi N, Valkonen M, Venet L, Wang Y, Weiss N, Wodzinski M, Xiang Y, Xu Y, Yan Y, Yushkevic P, Zhao S, Muñoz-Barrutia A (2020) ANHIR: Automatic Non-rigid Histological Image Registration Challenge. IEEE Trans Med Imaging 1–10

Kuckertz S, Papenberg N, Honegger J, Morgas T, Haas B, Heldmann S (2020) Deep learning based CT-CBCT image registration for adaptive radio therapy. Proceedings of SPIE Medical Imaging: Image Processing. 113130Q:pp 1–6

Kuckertz S, Papenberg N, Honegger J, Morgas T, Haas B, Heldmann S (2020) Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy. In: Špiclin Ž, McClelland J, Kybic J, Goksel O (eds) Biomedical Image Registration. LNCS 12120, pp 44–53

Lange A, Heldmann S (2020) Intensity-Based 2D-3D Registration Using Normalized Gradient Fields. In: Tolxdorff T, Deserno TM, Handels H, Maier A, Maier-Hein KH, Palm C (eds) Bildverarbeitung für die Medizin 2020. Springer Fachmedien Wiesbaden, pp 163–168

Lange A, Heldmann S (2020) Multilevel 2D-3D Intensity-Based Image Registration. In: Špiclin Ž, McClelland J, Kybic J, Goksel O (eds) Biomedical Image Registration. LNCS 12120, pp 57–66

2019

Grob D, Oostveen L, Rühaak J, Heldmann S, Mohr B, Michielsen K, Dorn S, Prokop M, Kachelrieβ M, Brink M, Sechopoulos I (2019) Accuracy of registration algorithms in subtraction CT of the lungs: A digital phantom study. Med Phys 46(5):2264–2274

Hering A, Heldmann S (2019) Unsupervised Learning for Large Motion Thoracic CT Follow-Up Registration. Proceedings of SPIE Medical Imaging: Image Processing. 109491B:pp 1–7

Hering A, Kuckertz S, Heldmann S, Heinrich MP (2019) Enhancing Label-Driven Deep Deformable Image Registration with Local Distance Metrics for State-of-the-Art Cardiac Motion Tracking. Bildverarbeitung für die Medizin 2019. pp 309–314

Hering A, Kuckertz S, Heldmann S, Heinrich MP (2019) Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans. Int J CARS 14(11):1901–1912

Hering A, van Ginneken B, Heldmann S (2019) mlVIRNET: Multilevel Variational Image Registration Network. In: Shen D, Liu T, Peters TM, Staib LH, Essert C, Zhou S, Yap P-T, Khan A (eds) Proceeding of Medical Image Computing and Computer Assisted Intervention. LNCS 11769, pp 257–265

Jäckle S, Strehlow J, Heldmann S (2019) Shape Sensing with Fiber Bragg Grating Sensors. Bildverarbeitung für die Medizin 2019. pp 258–263

2018

Gregori J, Cornelissen C, S. H, and Treiber MRS, Heldmann S, Klein J, Opfer R, Spies L, Gass A, Ziemsen T, Kitzler H, Weiler F (2018) Feasibility of fully automated atrophy measurement of the upper cervical spinal cord for group analyses and patient-individual diagnosis support in MS. 34th Congress of ECTRIMS – European Committee for Treatment and Research in Multiple Sclerosis. 34th Congress of ECTRIMS – European Committee for Treatment and Research in Multiple Sclerosis (Abstract: A-0950-0023-00837)

Jäckle S, Heldmann S (2018) Rigid Lens – Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scans. Image Analysis for Moving Organ, Breast, and Thoracic Images. pp 272–283

Weiler F, Klein J, Gregori J, Spiess L, Hildebrandt H, Heldmann S (2018) Fully automatic quantification of mean-upper cervical cord area: Agreement with multiple human raters. International Journal of Computer Assisted Radiology and Surgery. pp 150–151

2017

Lotz JM, Hoffmann F, Lotz J, Heldmann S, Trede D, Oetjen J, Becker M, Ernst G, Maas P, Alexandrov T, Guntinas-Lichius O, Thiele H, von Eggeling F (2017) Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition. Biochim Biophys Acta 1865(7):946–956

Rühaak J, Polzin T, Heldmann S, Simpson IJA, Handels H, Modersitzki J, Heinrich MP (2017) Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration. IEEE Trans Med Imaging 36(8):1746–1757

Weiler F, Hallmann M, Schwier M, Hildebrandt H, Gregori J, Spiess L, Klein J, Heldmann S (2017) Fully automated detection, segmentation and quantification of mean cross-sectional area of the spinal cord. Proceedings of the 7thth joint ECTRIMS – ACTRIMS Meeting. P384

2016

Derksen A, König L, Meine H, Heldmann S (2016) A Joint Registration and Segmentation Approach for Large Bladder Deformations in Adaptive Radiotherapy. Medical Physics: Proceedings of the AAPM 58th annual meeting, Washington, DC. American Association of Physicists in Medicine, 3429

Lotz J, Olesch J, Müller B, Polzin T, Galuschka P, Lotz JM, Heldmann S, Laue H, González-Vallinas M, Warth A, Lahrmann B, Grabe N, Sedlaczek O, Breuhahn K, Modersitzki J (2016) Patch-Based Nonlinear Image Registration for Gigapixel Whole Slide Images. IEEE Transactions on Biomedical Engineering 63(9):1812–1819

Lotz J, Olesch J, Müller B, Polzin T, Galuschka P, Lotz JM, Heldmann S, Laue H, Warth A, Lahrmann B, Grabe N, Sedlaczek O, Breuhahn K, Modersitzki J (2016) Patch-Based Nonlinear Image Registration for Gigapixel Whole Slide Images. IEEE Trans Biomed Eng 63(9):1812–1819

2015

Chen K, Derksen A, Heldmann S, Hallmann M, Berkels B (2015) Deformable Image Registration with Automatic Non-Correspondence Detection. Proc. of 5th International Conference on Scale Space Methods and Variational Methods in Computer Vision. LNCS 9087, pp 360–371

Derksen A, Heldmann S, Polzin T, Berkels B (2015) Image Registration with Sliding Motion Constraints for 4D CT Motion Correction. Bildverarbeitung für die Medizin 2015. Springer Berlin Heidelberg, pp 335–340

Heldmann S, Polzin T, Derksen A, Berkels B (2015) An image registration framework for sliding motion with piecewise smooth deformations. Proc. of 5th International Conference on Scale Space Methods and Variational Methods in Computer Vision. LNCS 9087, pp 335–347

König L, Derksen A, Heldmann S, Papenberg N, Modersitzki J, Haas B (2015) OC-0409: Deformable image registration with guaranteed local rigidity. Radiotherapy and Oncology: Proceedings of the 3rd ESTRO Forum. pp S197–S198

Modersitzki J, Heldmann S, Papenberg N (2015) Nonlinear Registration Via Displacement Fields. In: Toga AW (ed) Brain Mapping. Academic Press, Waltham, pp 307–314

Papenberg N, König L, Heldmann S, Derksen A, Modersitzki J, Haas B (2015) A Locally Variable Transformation Model for Deformable Image Registration Using Tissue Properties. Varian Research Partnership Symposium. Atlanta, Georgia, USA

Rühaak J, Derksen A, Heldmann S, Hallmann M, Meine H (2015) Accurate CT-MR image registration for deep brain stimulation: a multi-observer evaluation study. Proceedings of SPIE Medical Imaging: Image Processing. 941337:pp 1–7

Vicari M, Heldmann S, Meine H, Hug F, Hennig J, Iblher N (2015) Quantitative Assessments of Facial Soft-Tissue Mobility by means of Watershed Segmentation and Constrained Elastic Registration in Upright Accelerated 3D MRI. Proceedings of the 23rd Annual Meeting ISMRM. 4204

2014

Chen K, Heldmann S, Rühaak J, Hallmann M (2014) Construction of Average STN Atlas using Image Registration and Reconstruction. Proc. MICCAI 2014 Workshop on Deep Brain Stimulation Methodological Challenges – 2nd Edition. Boston, USA, pp 1–9

Lotz J, Berger J, Thiele H, Olesch J, Müller B, Breuhahn K, Warth A, Grabe N, Lahrmann B, Sedlaczek O, Heldmann S (2014) Elastic image registration on whole slide images for digital double staining and 3D reconstruction. European Molecular Imaging Meeting – EMIM. Poster Submission at the European Molecular Imaging Meeting – EMIM

Lotz J, Berger J, Müller B, Breuhahn K, Grabe N, Heldmann S, Homeyer A, Lahrmann B, Laue H, Olesch J, Schwier M, Sedlaczek O, Warth A (2014) Zooming in: High Resolution 3D Reconstruction of Differently Stained Histological Whole Slide Images. Proceeding of SPIE Medical Imaging: Digital Pathology. 904104:pp 1–7

Thiele H, Heldmann S, Trede D, Strehlow J, Wirtz S, Dreher W, Berger J, Oetjen J, Kobarg JH, Fischer B, Maass P (2014) 2D and 3D MALDI-imaging: Conceptual strategies for visualization and data mining. Biochim Biophys Acta 1844(1):117–137

2013

Oetjen J, Aichler M, Trede D, Strehlow J, Berger J, Heldmann S, Becker M, Gottschalk M, Kobarg JH, Wirtz S, Schiffler S, Thiele H, Walch A, Maass P, Alexandrov T (2013) MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation. J Proteomics 90:52–60

Polzin T, Rühaak J, Werner R, Strehlow J, Heldmann S, Handels H, Modersitzki J (2013) Combining Automatic Landmark Detection and Variational Methods for Lung CT Registration. Proc. Fifth International MICCAI Workshop on Pulmonary Image Analysis (PIA 2013)

Rühaak J, König L, Hallmann M, Papenberg N, Heldmann S, Schumacher H, Fischer B (2013) A Fully Parallel Algorithm for Multimodal Image Registration Using Normalized Gradient Fields. IEEE International Symposium on Biomedical Imaging: From Nano to Macro. San Francisco, California, USA, pp 572–575

Rühaak J, Heldmann S, Kipshagen T, Fischer B (2013) Highly Accurate Fast Lung CT Registration. Proceedings of SPIE Medical Imaging. 86690Y:pp 1–9

Ruhaak J, Heldmann S, Kipshagen T, Fischer B (2013) Highly Accurate Fast Lung CT Registration. Proceedings of SPIE Medical Imaging: Image Processing. SPIE Medical Imaging 2013: Image Processing, 86690Y

2012

Thiele H, Heldmann S, Fischer B (2012) 3D Visualisierung von Organismen. In: Goltz U, Magnor M, Appelrath H-J, Matthies HK, Balke W-T, Wolf L (eds) Proceedings der INFORMATIK 2012. GI-Editon Lecture Notes in Informatics 208, pp 1535–1545

Trede D, Schiffler S, Becker M, Wirtz S, Steinhorst K, Strehlow J, Aichler M, Kobarg JH, Oetjen J, Heldmann S, Walch A, Thiele H, Maass P, Alexandrov T (2012) Exploring 3D MALDI imaging mass spectrometry data: 3D spatial segmentation of mouse kidney. Anal Chem 84(14):6079–6087

2011

Olesch J, Beuthien B, Heldmann S, Papenberg N, Fischer B (2011) Fast intra-operative nonlinear registration of 3D-CT to tracked, selected 2D-ultrasound slices. Proceeding SPIE Medical Imaging. 79642R:pp 1–6

Rühaak J, Heldmann S, Fischer B (2011) Improving Lung Registration by Incorporating Anatomical Knowledge: A Variational Approach. Proc. Fourth International MICCAI Workshop on Pulmonary Image Analysis (PULMO 2011). pp 147–156

Ruhaak J, Heldmann S, Fischer B (2011) Improving Lung Registration by Incorporating Anatomical Knowledge: A Variational Approach. Proc. Fourth International MICCAI Workshop on Pulmonary Image Analysis (PULMO 2011). Proc. Fourth International MICCAI Workshop on Pulmonary Image Analysis (PULMO 2011)

2010

Beuthien B, Papenberg N, Heldmann S, Fischer B (2010) Volume-constrained image registration for pre- and post-operative CT liver data. Proceedings of SPIE Medical Imaging. Medical Imaging 2010: Image Processing, San Diego, California, USA, February 14-16, 2010, 762339:pp 1–8

Heldmann S (2010) Multimodal Registration of MR Images with a Novel Least-squares Distance Measure. Proceedings of SPIE Medical Imaging: Image Processing. 76230A:pp 1–8

Heldmann S, Beuthien B, Olesch J, Papenberg N, Fischer B (2010) Improved Minimal-Invasive Laparoscopic Liver Surgery by Registration of 3D CT and 2D Ultrasound Slices. Proc. BMT, 2010. BMT 2010 – FAL-Sessions, Hot-Topic Sessions, Projektsessions (BMT 2010 – FAL-Sessions – Hot-Topic Se

Heldmann S, Beuthien B, Olesch J, Papenberg N, Fischer B (2010) Improved Minimal-Invasive Laparoscopic Liver Surgery by Registration of 3D CT and 2D Ultrasound Slices. Biomedizinische Technik

Papenberg N, Lange T, Heldmann S, Fischer B (2010) Bildregistrierung. In: Schlag PM, Eulenstein S, LAnge T (eds) Computerassistierte Chirurgie. Urban & Fischer, Elsevier, Münichen, pp 85–118

Papenberg N, Schumacher H, Heldmann S, Böhler T, van Straaten D, Wirtz S (2010) Multimodale Registrierung von Knochen-Szintigraphien und Röntgenbildern. Bildverarbeitung für die Medizin. pp 335–339

2009

Ens K, Heldmann S, Modersitzki J, Fischer B (2009) Improving an affine and non-linear image registration and/or segmentation task by incorporating characteristics of the displacement field. Proceedings of SPIE Medical Imaging. 725932:pp 1–8

Haber E, Heldmann S, Modersitzki J (2009) A Computational Framework for Image-Based Constrained Registration. Linear Algebra and Its Applications 431(3-4):459–470

Haber E, Heldmann S, Modersitzki J (2009) A Scale-Space Approach to Landmark Constrained Image Registration. Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision. pp 612–623

Heldmann S, Papenberg N (2009) A Scale-Space Approach for Image Registration of Vessel Structures. Bildverarbeitung für die Medizin. pp 137–141

Heldmann S, Zidowitz S (2009) Elastic Registration of Multiphase CT Images of Liver. In: Pluim JPW, Dawant BM (eds) Proceedings of SPIE Medical Imaging: Image Processing. Proceedings of the SPIE, 72591H:pp 1–12

Lange T, Papenberg N, Heldmann S, Modersitzki J, Fischer B, Lamecker H, Schlag PM (2009) 3D ultrasound-CT registration of the liver using combined landmark-intensity information. Int J CARS 4(1):79–88

2008

Haber E, Heldmann S, Modersitzki J (2008) Adaptive Mesh Refinement for Nonparametric Image Registration. SIAM J Sci Comput 30(6):3012–3027

2007

Haber E, Heldmann S, Ascher U (2007) Adaptive finite volume method for distributed non-smooth parameter identification. Inverse Problems 23(4):1659–1676

Papenberg N, Schumacher H, Heldmann S, Wirtz S, Bommersheim S, Ens K, Modersitzki J, Fischer B (2007) A Fast and Flexible Image Registration Toolbox – Design and Implementation of the general approach. Bildverarbeitung für die Medizin. SPIE Medical Imaging, pp 106–110

2006

Heldmann S (2006) Non-Linear Registration based on Mutual Information. Ph.D. thesis. Logos Verlag Berlin