Fraunhofer Institute for Digital Medicine MEVISResearch Interests
- Image Analysis & Artificial Intelligence
- Deep Learning
- Image Segmentation
Felix Thielke
Publications
2025
Tappermann C, Thielke F, Graefen M, Haese A, Hahn HK, Hohenhorst JL, Meine H (2025) Deep Learning-Based Outcome Prediction from Endoscopic Videos for Robot-Assisted Radical Prostatectomy. In: Colliot O, Mitra J (eds) Proceedings of SPIE Medical Imaging 2025: Image Processing. SPIE, 134060L
2024
Cangalovic VS, Thielke F, Meine H (2024) Comparative evaluation of uncertainty estimation and decomposition methods on liver segmentation. Int J CARS 19(2):253–260
Kock F, Thielke F, Abolmaali N, Meine H, Schenk A (2024) Suitability of DNN-based vessel segmentation for SIRT planning. Int J CARS 19(2):233–240
2023
Gerken A, Thielke F, Meine H, Singer S, Froelich MF, Becker LS, Hinrichs J, Schenk A (2023) Importance of the late hepatobiliary phase of DCE-MRI for automatic liver lesion detection and segmentation. European Congress of Radiology
Thielke F, Kock F, Hänsch A, Abolmaali N, Schenk A, Meine H (2023) Combining arterial and venous CT scans in a multi-encoder network for improved hepatic vessel segmentation. Proc. SPIE Medical Imaging 2023: Image Processing. Proc.SPIE 12464, 124640B
2022
Adam J, Agethen N, Bohnsack R, Finzel R, Günnemann T, Philipp L, Plutat M, Rink M, Xue T, Thielke F, Meine H (2022) Extraction of Kidney Anatomy Based on a 3D U-ResNet with Overlap-Tile Strategy. Kidney and Kidney Tumor Segmentation. KiTS 2021. Lecture Notes in Computer Science
Hänsch A, Thielke F, Meine H, Rennebaum S, Froelich MF, Becker LS, Hinrichs JB, Schenk A (2022) Robust Liver Segmentation with Deep Learning Across DCE-MRI Contrast Phases. In: Maier-Hein K, Deserno TM, Handels H, Maier A, Palm C, Tolxdorff T (eds) Bildverarbeitung für die Medizin 2022. Springer Fachmedien Wiesbaden, Wiesbaden, pp 13–18
Hänsch A, Chlebus G, Meine H, Thielke F, Kock F, Paulus T, Abolmaali N, Schenk A (2022) Improving automatic liver tumor segmentation in late-phase MRI using multi-model training and 3D convolutional neural networks. Sci Rep 12:12262
Kock F, Chlebus G, Thielke F, Schenk A, Meine H (2022) Hepatic artery segmentation with 3D convolutional neural networks. Proc. SPIE Medical Imaging 2022: Computer-Aided Diagnosis. Proc. SPIE 12033, pp 437–441
Kock F, Thielke F, Grzegorz C, Meine H (2022) Confidence Histograms for Model Reliability Analysis and Temperature Calibration. Proceedings of the International Conference on Medical Imaging with Deep Learning (MIDL 2022). pp 741–759
Thielke F, Kock F, Hänsch A, Georgii J, Abolmaali N, Endo I, Meine H, Schenk A (2022) Improving deep learning based liver vessel segmentation using automated connectivity analysis. Proc. SPIE Medical Imaging 2022: Image Processing. Proc. SPIE 12032, pp 886–892