Fraunhofer Institute for Digital Medicine MEVISResearch Interests
- deep learning methods, tools, and workflows
- automatic and interactive image analysis
- uncertainty quantification
- active learning
Dr. Hans Meine
Hans Meine studied computer science and received his PhD from the University of Hamburg in 2008 for his fundamental research on image segmentation algorithms and data structures. In 2011, he joined Fraunhofer MEVIS, where he is now responsible for coordinating strategic developments across various projects, medical applications, and imaging modalities. His research interests not only include core image analysis topics such as segmentation of organs, tumors and vessels, but also tooling for collaborative, interdisciplinary research.
Publications
2024
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
Lassen-Schmidt B, Baessler B, Gutberlet M, Berger J, Brendel JM, Bucher AM, Emrich T, Fervers P, Kottlors J, Kuhl P, May MS, Penzkofer T, Persigehl T, Renz D, Sähn M-J, Siegler L, Kohlmann P, Köhn A, Link F, Meine H, Thiemann MT, Hahn HK, Sieren MM (2024) Cooperative AI training for cardiothoracic segmentation in computed tomography: An iterative multi-center annotation approach. European Journal of Radiology 176:111534
Rovedo P, Meine H, Hucker P, Taghizadeh E, Izadpanah K, Zaitsev M, Lange T (2024) Time‐Resolved Quantification of Patellofemoral Cartilage Deformation in Response to Loading and Unloading via Dynamic MRI With Prospective Motion Correction. Magnetic Resonance Imaging 60(1):175–183
2023
Bilic P, Christ P, Li HB, Vorontsov E, Ben-Cohen A, Kaissis G, Szeskin A, Jacobs C, Mamani GEH, Chartrand G, Lohöfer F, Holch JW, Sommer W, Hofmann F, Hostettler A, Lev-Cohain N, Drozdzal M, Amitai MM, Vivanti R, Sosna J, Ezhov I, Sekuboyina A, Navarro F, Kofler F, Paetzold JC, Shit S, Hu X, Lipková J, Rempfler M, Piraud M, Kirschke J, Wiestler B, Zhang Z, Hülsemeyer C, Beetz M, Ettlinger F, Antonelli M, Bae W, Bellver M, Bi L, Chen H, Chlebus G, Dam EB, Dou Q, Fu C-W, Georgescu B, Giró-i-Nieto X, Gruen F, Han X, Heng P-A, Hesser J, Moltz JH, Igel C, Isensee F, Jäger P, Jia F, Kaluva KC, Khened M, Kim I, Kim J-H, Kim S, Kohl S, Konopczynski T, Kori A, Krishnamurthi G, Li F, Li H, Li J, Li X, Lowengrub J, Ma J, Maier-Hein K, Maninis K-K, Meine H, Merhof D, Pai A, Perslev M, Petersen J, Pont-Tuset J, Qi J, Qi X, Rippel O, Roth K, Sarasua I, Schenk A, Shen Z, Torres J, Wachinger C, Wang C, Weninger L, Wu J, Xu D, Yang X, Yu SC-H, Yuan Y, Yue M, Zhang L, Cardoso J, Bakas S, Braren R, Heinemann V, Pal C, Tang A, Kadoury S, Soler L, van Ginneken B, Greenspan H, Joskowicz L, Menze B (2023) The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Analysis 84:102680
Cangalovic VS, Thielke F, Meine H (2023) Comparative evaluation of uncertainty estimation and decomposition methods on liver segmentation. Int J CARS online first
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
Kock F, Thielke F, Abolmaali N, Meine H, Schenk A (2023) Suitability of DNN-based vessel segmentation for SIRT planning. Int J CARS
Meine H, Brandenburg LS, Detering M, Weingart P, Metzger MC, Georgii J (2023) AI-based characterization of partially edentulous jaws in panoramic x-rays. Int J CARS. S76
Mou Y, Li F, Weber S, Haneef S, Meine H, Caldeira L, Jaberansary M, Welten S, Yediel Ucer Y, Prause G, Decker S, Beyan O, Kirsten T (2023) Distributed Privacy-Preserving Data Analysis in NFDI4Health with the Personal Health Train. In: Sure-Vetter Y, Goble C (eds) Proceedings of the 1st Conference on Research Data Infrastructure (CoRDI) – Connecting Communities. pp 1–5
Siegel M, Maier P, Taghizadeh E, Fuchs A, Yilmaz T, Meine H, Schmal H, Lange T, Izadpanah K (2023) Change in Descriptive Kinematic Parameters of Patients with Patellofemoral Instability When Compared to Individuals with Healthy Knees—A 3D MRI In Vivo Analysis. Jcm 12(5):1917
Siegel M, Taghizadeh E, Lange T, Fuchs A, Yilmaz T, Maier P, Meine H, Schmal H, Izadpanah K (2023) Influence of Medial Patellofemoral Ligament Reconstruction on Patellofemoral Contact in Patients With Low-Flexion Patellar Instability: An MRI Study. Orthopaedic Journal of Sports Medicine 11(5):232596712311602
Siegel M, Taghizadeh E, Fuchs A, Maier P, Schmal H, Lange T, Yilmaz T, Meine H, Izadpanah K (2023) Einfluss der Quadrizepsmuskulatur auf den patellofemoralen Kontaktmechanismus bei Patienten mit strecknaher patellofemoraler Instabilität nach MPFL-Rekonstruktion. Die Orthopädie 52(10):834–842
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
Wagner M, Müller-Stich B-P, Kisilenko A, Tran D, Heger P, Mündermann L, Lubotsky DM, Müller B, Davitashvili T, Capek M, Reinke A, Reid C, Yu T, Vardazaryan A, Nwoye CI, Padoy N, Liu X, Lee E-J, Disch C, Meine H, Xia T, Jia F, Kondo S, Reiter W, Jin Y, Long Y, Jiang M, Dou Q, Heng PA, Twick I, Kirtac K, Hosgor E, Bolmgren JL, Stenzel M, von Siemens B, Zhao L, Ge Z, Sun H, Xie D, Guo M, Liu D, Kenngott HG, Nickel F, Frankenberg M von, Mathis-Ullrich F, Kopp-Schneider A, Maier-Hein L, Speidel S, Bodenstedt S (2023) Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark. Medical Image Analysis 86:102770
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
Brandenburg LS, Berger L, Schwarz SJ, Meine H, Weingart JV, Steybe D, Spies BC, Burkhardt F, Schlager S, Metzger MC (2022) Reconstruction of dental roots for implant planning purposes: a feasibility study. Int J CARS (2022) 17:1957–1968
Chlebus G, Schenk A, Hahn HK, Van Ginneken B, Meine H (2022) Robust Segmentation Models Using an Uncertainty Slice Sampling-Based Annotation Workflow. IEEE Access 10:4728–4738
Frodl A, Lange T, Siegel M, Meine H, Taghizadeh E, Schmal H, Izadpanah K (2022) Individual Influence of Trochlear Dysplasia on Patellofemoral Kinematics after Isolated MPFL Reconstruction. J Pers Med 12(12):2049
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
Konradi J, Zajber M, Betz U, Drees P, Gerken A, Meine H (2022) AI-based detection of aspiration for video-endoscopy with visual aids in meaningful frames to interpret the model outcome. Sensors 22(23):9468
Konradi J, Zajber M, Stegner S, Czysch C, Corsten S, Betz U, Disch C, Hänsch A, Meine H (2022) Nutzung von künstlicher Intelligenz (KI) in der endoskopischen Schluckdiagnostik. Erste Ergebnisse zur Genauigkeit der KI-basierten Aspirations-Detektionsleistung. Sprachtherapie aktuell: Forschung – Wissen – Transfer. XXXIV. Workshop Klinische Linguistik. pp e2022–2002
Sack J, Nitsch J, Meine H, Kikinis R, Halle M, Rutherford A (2022) Quantitative Analysis of Liver Disease Using MRI-Based Radiomic Features of the Liver and Spleen. J Imaging 8(10):277
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
2021
Meyer A, Chlebus G, Rak M, Schindele D, Schostak M, van Ginneken B, Schenk A, Meine H, Hahn HK, Schreiber A, Hansen C (2021) Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI. Comput Methods Programs Biomed 200:105821
Nitsch J, Sack J, Halle MW, Moltz JH, Wall A, Rutherford AE, Kikinis R, Meine H (2021) MRI-based radiomic feature analysis of end-stage liver disease for severity stratification. Int J CARS 16(3):457–466
2020
Izadpanah K, Meine H, Kubosch J, Lang G, Fuchs A, Maier D, Ogon P, Südkamp NP, Feucht MJ (2020) Fluoroscopic guided tunnel placement during medial patellofemoral ligament reconstruction is not accurate in patients with severe trochlear dysplasia. Knee Surg Sports Traumatol Arthrosc 28(3):759–766
Klein J, Wenzel M, Romberg D, Köhn A, Kohlmann P, Link F, Hänsch A, Dicken V, Stein R, Haase J, Schreiber A, Hahn H, Meine H (2020) QuantMed: Component-based DL platform for translational research. Proceedings of SPIE Medical Imaging: Imaging Informatics for Healthcare, Research, and Applications. 113180U:pp 1–8
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
2019
Chlebus G, Meine H, Thoduka S, Abolmaali N, van Ginneken B, Hahn HK, Schenk A (2019) Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections. PLoS ONE 14(5):e0217228
Chlebus G, Abolmaali N, Schenk A, Meine H (2019) Relevance analysis of MRI sequences for automatic liver tumor segmentation. Proceedings of Medical Imaging with Deep Learning (MIDL 2019). pp 1–4
Lange T, Taghizadeh E, Knowles BR, Südkamp NP, Zaitsev M, Meine H, Izadpanah K (2019) Quantification of patellofemoral cartilage deformation and contact area changes in response to static loading via high‐resolution MRI with prospective motion correction. J Magn Reson Imaging 50(5):1561–1570
Mayr M, Tayfun Y, Bode G, Meine H, Georgii J, Südkamp N, Izadpanah K (2019) In vivo Kinematik von Knorpel- und Meniskuskontaktflächen des Kniegelenks unter Last. Proc. of GOTS
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
Nitsch J, Klein J, Dammann D, Wrede K, Gembruch O, Moltz J, Meine H, Sure U, Kikinis R, Miller D (2019) Automatic and Efficient MRI-US Segmentations for Improving Intraoperative Image Fusion in Image-Guided Neurosurgery. Neuroimage Clin 22:101766
Nitsch J, Klein J, Moltz JH, Miller D, Sure U, Kikinis R, Meine H (2019) Neural-network-based automatic segmentation of cerebral ultrasound images for improving image-guided neurosurgery. Proceedings of SPIE Medical Imaging: Image-Guided Procedures, Robotic Interventions, and Modeling. 109511N:pp 1–7
2018
Chlebus G, Schenk A, Moltz JH, van Ginneken B, Hahn HK, Meine H (2018) Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing. Sci Rep 8:15497
Chlebus G, Meine H, Abolmaali N, Schenk A (2018) Automatic Liver and Tumor Segmentation in Late-Phase MRI Using Fully Convolutional Neural Networks. Proceedings of CURAC. pp 195–200
Haensch A, Dicken V, Gass T, Morgas T, Klein J, Meine H, Hahn HK (2018) Deep learning based segmentation of organs of the female pelvis in CBCT scans for adaptive radiotherapy using CT and CBCT data. Proceedings of the 32nd International Congress and Exhibition of Computer Assisted Radiology and Surgery (CARS). pp 179–180
Hänsch A, Gass T, Morgas T, Haas B, Meine H, Klein J, Hahn HK (2018) Parotid gland segmentation with deep learning using clinical vs. curated training data. Radiotherapy and Oncology: Proceedings of ESTRO 37. pp S281–S282
Hänsch A, Schwier M, Gass T, Morgas T, Haas B, Dicken V, Meine H, Klein J, Hahn HK (2018) Evaluation of deep learning methods for parotid gland segmentation from CT images. J Med Imag 6(1):011005
Schenk A, Chlebus G, Meine H, Thoduka S, Abolmaali N (2018) Deep learning for liver segmentation and volumetry in late phase MRI. Proceedings of European Congress on Radiology (ECR). Springer, S474
2017
Chlebus G, Meine H, Moltz JH, Schenk A (2017) Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering. arXiv:1706.00842
Chlebus G, Schenk A, Thoduka S, Abolmaali N, Endo I, Meine H (2017) Comparison of Model Initialization Methods for Liver Segmentation using Statistical Shape Models. Proceedings of the 31st International Congress and Exhibition of Computer Assisted Radiology and Surgery (CARS). pp 215–216
Haensch A, Harz M, Schenk A, Endo I, Jacobs C, Hahn HK, Meine H (2017) Examining the robustness of liver segmentation using deep learning and unsupervised pre-training of a feature extractor. International Journal of Computer Assisted Radiology and Surgery. Springer International Publishing, pp 23–24
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
Meine H, Izadpanah K, Lange T (2016) Image Processing Pipeline for MRI-based In-vivo Cartilage Assessment under Load. In: Lemke H (ed) Computer Assisted Radiology and Surgery (CARS) 2016: Proceedings of the 30th Congress and Exhibition. Springer, S51+
Wang L, Chitiboi T, Meine H, Günther M, Hahn HK (2016) Principles and methods for automatic and semi-automatic tissue segmentation in MRI data. Magn Reson Mater Phy 29(2):95–110
2015
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 L, Hallmann M, Barrios Romero D, Wang L, Astrom M, Ryzhkov M, Nijlunsing R, Meine H (2014) Combining tubular tracking and skeletonization for fully-automatic and accurate lead localization in CT images. Proc. Computer Assisted Radiology and Surgery – Neurosurgery and ENT Surgery. pp 195–196
Demedts D, Hennemuth A, Meine H, Ojdanic D (2014) Web-based interactive visualization and assessment of medical images for clinical trials. Proc. Computer Assisted Radiology and Surgery – Display and Visualization. pp S85–S86
Heckel F, Meine H, Moltz JH, Kuhnigk J-M, Heverhagen JT, Kießling A, Buerke B, Hahn HK (2014) Segmentation-Based Partial Volume Correction for Volume Estimation of Solid Lesions in CT. IEEE Trans Med Imaging 33(2):462–480
Heckel F, Moltz JH, Meine H, Geisler B, Kießling A, D'Anastasi M, Pinto dos Santos D, Theruvath AJ, Hahn HK (2014) On the Evaluation of Segmentation Editing Tools. SPIE J Med Imag 1(3):034005: 1–17
Rudyanto RD, Kerkstra S, van Rikxoort EM, Fetita C, Brillet PY, Lefevre C, Xue W, Zhu X, Liang J, Oksüz I, Unay D, Kadipaşaoğlu K, Estépar RS, Ross JC, Washko GR, Prieto JC, Hoyos MH, Orkisz M, Meine H, Hüllebrand M, Stöcker C, Mir FL, Naranjo V, Villanueva E, Staring M, Xiao C, Stoel BC, Fabijanska A, Smistad E, Elster AC, Lindseth F, Foruzan AH, Kiros R, Popuri K, Cobzas D, Jimenez-Carretero D, Santos A, Ledesma-Carbayo MJ, Helmberger M, Urschler M, Pienn M, Bosboom DG, Campo A, Prokop M, de Jong PA, Ortiz-de-Solorzano C, Muñoz-Barrutia A, van Ginneken B (2014) Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study. Med Image Anal 18(7):1217–1232