Sven Kuckertz, M.Sc.

  • Research Scientist
  • Image Registration

Publications

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
Kuckertz S, Heldmann S, Moltz JH (2023) Efficient Registration of Longitudinal Studies for Follow-Up Lesion Assessment by Exploiting Redundancy and Composition of Deformations. Proceedings of the First MICCAI Workshop on Lesion Evaluation and Assessment with Follow-up (LEAF 2023). Springer, pp 91–99

2022

Kuckertz S, Klein J, Engel C, Geisler B, Krass S, Heldmann S (2022) Fully automated longitudinal tracking and in-depth analysis of the entire tumor burden: unlocking the complexity. Proc. SPIE Medical Imaging 2022: Computer-Aided Diagnosis. Proc. SPIE 12033, pp 455–459

2021

Kuckertz S, Weiler F, Matusche B, Lukas C, Spies L, Klein J, Heldmann S (2021) A system for fully automated monitoring of lesion evolution over time in multiple sclerosis. Proceedings of SPIE Medical Imaging: Computer-Aided Diagnosis. 115972D

2020

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

2019

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

2018

Kuckertz S (2018) Schwach überwachtes Lernen nichtlinearer medizinischer Bildregistrierung mit neuronalen Faltungsnetzwerken. Master's thesis