Fraunhofer Institute for Digital Medicine MEVIS- Research Scientist
- Image Registration
Dr. Alessa Hering, M.Sc.
Publications
2022
Hering AD (2022) Deep-Learning-based Image Registration and Tumor Follow-Up Analysis. Ph.D. thesis
Peisen F, Hänsch A, Hering A, Brendlin AS, Afat S, Nikolaou K, Gatidis S, Eigentler T, Amaral T, Moltz JH, Othman AE (2022) Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy. Cancers 14(12):2992
Roth HR, Xu Z, Tor Diez C, Sanchez Jacob R, Zember J, Molto J, Li W, Xu S, Turkbey B, Turkbey E, Yang D, Harouni A, Rieke N, Hu S, Isensee F, Tang C, Yu Q, Sölter J, Zheng T, Liauchuk V, Zhou Z, Moltz JH, Oliveira B, Xia Y, Maier-Hein K, Li Q, Husch A, Zhang L, Kovalev V, Kang L, Hering A, Vilaça J, Flores M, Xu D, Wood B, Linguraru MG (2022) Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge. Medical Image Analysis 82:102605
2021
Hering A, Häger S, Moltz J, Lessmann N, Heldmann S, van Ginneken B (2021) CNN-based lung CT registration with multiple anatomical constraints. Med Image Anal 72:102139
Hering A, Peisen F, Amaral T, Gatidis S, Eigentler T, Othman A, Moltz JH (2021) Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies. Proceedings of Machine Learning Research (MIDL 2021). pp 312–326
2020
Lassen-Schmidt B, Hering A, Krass S, Meine H (2020) Automatic segmentation of the pulmonary lobes with a 3D u-net and optimized loss function. Medical Imaging with Deep Learning (MIDL 2020). arXiv:2006.00083v1
Sieren MM, Brenne F, Hering A, Kienapfel H, Gebauer N, Oechtering TH, Fürschke A, Wegner F, Stahlberg E, Heldmann S, Barkhausen J, Frydrychowicz A (2020) Rapid study assessment in follow-up whole-body computed tomography in patients with multiple myeloma using a dedicated bone subtraction software. European Radiology 30:3198–3209
2019
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
Meine H, Hering A (2019) Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor. Proceedings of Medical Imaging with Deep Learning (MIDL 2019). pp 1–4