Fraunhofer Institute for Digital Medicine MEVIS(Alumna)
Dr. Alessa Hering, M.Sc.
Publications
2025
de Grauw MJJ, Scholten ET, Smit EJ, Rutten MJCM, Prokop M, van Ginneken B, Hering A (2025) The ULS23 challenge: A baseline model and benchmark dataset for 3D universal lesion segmentation in computed tomography. Med Image Anal 102:103525
Peisen F, Gerken A, Hering A, Dahm I, Nikolaou K, Gatidis S, Eigentler TK, Amaral T, Moltz JH, Othman AE (2025) Correction: Peisen et al. Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors? Cancers 2024, 16, 2669. Cancers 17(1)
2024
Dahm IC, Kolb M, Altmann S, Nikolaou K, Gatidis S, Othman AE, Hering A, Moltz JH, Peisen F (2024) Reliability of Automated RECIST 1.1 and Volumetric RECIST Target Lesion Response Evaluation in Follow-Up CT—A Multi-Center, Multi-Observer Reading Study. Cancers 16(23):4009
Hering A, de Boer S, Saha A, Twilt JJ, Heinrich MP, Yakar D, de Rooij M, Huisman H, Bosma JS (2024) Deformable MRI Sequence Registration for AI-Based Prostate Cancer Diagnosis. In: Modat M Simpson I. Špiclin Ž. Bastiaansen W. Hering A. Mok T.C.W. (ed) Biomedical Image Registration. WBIR 2024. LNCS, pp 148–162
Hering A, Westphal M, Gerken A, Almansour H, Maurer M, Geisler B, Kohlbrandt T, Eigentler T, Amaral T, Lessmann N, Gatidis S, Hahn H, Nikolaou K, Othman A, Moltz J, Peisen F (2024) Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow. International Journal of Computer Assisted Radiology and Surgery 19:1689–1697
Kohlbrandt T, Moltz J, Heldmann S, Hering A, Lellmann J (2024) Joint Learning of Image Registration and Change Detection for Lung CT Images. In: Maier A, Deserno TM, Handels H, Maier-Hein K, Palm C, Tolxdorff T (eds) Proceedings of German Conference on Medical Image Computing, BVM 2024. Informatik aktuell, pp 46–51
Peisen F, Gerken A, Hering A, Dahm I, Nikolaou K, Gatidis S, Eigentler TK, Amaral T, Moltz JH, Othman AE (2024) Can Delta Radiomics Improve the Prediction of Best Overall Response, Progression-Free Survival, and Overall Survival of Melanoma Patients Treated with Immune Checkpoint Inhibitors? Cancers 16(15):2669
2023
Hering A, Hansen L, Mok TCW, Chung ACS, Siebert H, Hager S, Lange A, Kuckertz S, Heldmann S, Shao W, Vesal S, Rusu M, Sonn G, Estienne T, Vakalopoulou M, Han L, Huang Y, Yap P-T, Brudfors M, Balbastre Y, Joutard S, Modat M, Lifshitz G, Raviv D, Lv J, Li Q, Jaouen V, Visvikis D, Fourcade C, Rubeaux M, Pan W, Xu Z, Jian B, De Benetti F, Wodzinski M, Gunnarsson N, Sjolund J, Grzech D, Qiu H, Li Z, Thorley A, Duan J, Grosbrohmer C, Hoopes A, Reinertsen I, Xiao Y, Landman B, Huo Y, Murphy K, Lessmann N, van Ginneken B, Dalca AV, Heinrich MP (2023) Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. IEEE Trans Med Imaging 42(3):697–712
Peisen F, Gerken A, Hering A, Dahm I, Nikolaou K, Gatidis S, Eigentler TK, Amaral T, Moltz JH, Othman AE (2023) Can Whole-Body Baseline CT Radiomics Add Information to the Prediction of Best Response, Progression-Free Survival, and Overall Survival of Stage IV Melanoma Patients Receiving First-Line Targeted Therapy: A Retrospective Register Study. Diagnostics 13(20):3210
Woo J, Hering A, Silva W, Li X, Fu H, et al. (2023) Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops. Springer, Cham, LNCS 14394
2022
Hansen L, Hering A, Großbröhmer C, Heinrich MP (2022) Continuous benchmarking in medical image registration – review of the current state of the Learn2Reg challenge. International Conference on Medical Imaging with Deep Learning (MIDL 2022)
Hering A, Peisen F, Moltz J (2022) Towards more efficient tumor follow-up assessment using AI assistance. International Conference on Medical Imaging with Deep Learning (MIDL 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. Med Image Anal 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