Dr. Jan Hendrik Moltz

  • Research Scientist
  • Medical Image Analysis



Enke JS, Moltz JH, D'Anastasi M, Kunz WG, Schmidt C, Maurus S, Mühlberg A, Katzmann A, Sühling M, Hahn H, Nörenberg D, Huber T (2022) Radiomics Features of the Spleen as Surrogates for CT-Based Lymphoma Diagnosis and Subtype Differentiation. Cancers 14(3):713
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
Sieren MM, Widmann C, Weiss N, Moltz JH, Link F, Wegner F, Stahlberg E, Horn M, Oechtering TH, Goltz JP, Barkhausen J, Frydrychowicz A (2022) Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach. European Radiology 32:690–701


Gebauer L, Moltz JH, Mühlberg A, Holch JW, Huber T, Enke J, Jäger N, Haas M, Kruger S, Boeck S, Sühling M, Katzmann A, Hahn H, Kunz WG, Heinemann V, Nörenberg D, Maurus S (2021) Quantitative Imaging Biomarkers of the Whole Liver Tumor Burden Improve Survival Prediction in Metastatic Pancreatic Cancer. Cancers 13(22):5732
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
Mühlberg A, Holch JW, Heinemann V, Huber T, Moltz J, Maurus S, Jäger N, Liu L, Froelich MF, Katzmann A, Gresser E, Taubmann O, Sühling M, Nörenberg D (2021) The relevance of CT-based geometric and radiomics analysis of whole liver tumor burden to predict survival of patients with metastatic colorectal cancer. Eur Radiol 31:834–846
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
Overhoff D, Kohlmann P, Frydrychowicz A, Gatidis S, Loewe C, Moltz J, Kuhnigk J-M, Gutberlet M, Winter H, Völker M, Hahn H, Schoenberg SO (2021) The International Radiomics Platform – An Initiative of the German and Austrian Radiological Societies – First Application Examples. Rofo 193(3):276–288


Hänsch A, Moltz JH, Geisler B, Engel C, Klein J, Genghi A, Schreier J, Morgas T, Haas B (2020) Hippocampus segmentation in CT using deep learning: impact of MR versus CT-based training contours. J Med Imaging 7(6):064001
Moltz JH, Hänsch A, Lassen-Schmidt B, Haas B, Genghi A, Schreier J, Morgas T, Klein J (2020) Learning a Loss Function for Segmentation: A Feasibility Study. IEEE International Symposium on Biomedical Imaging. pp 957–960


Bilic P, Christ PF, Vorontsov E, Chlebus G, Chen H, Dou Q, Fu C-W, Han X, Heng P-A, Hesser J, Kadoury S, Konopczynski T, Le M, Li C, Li X, Lipkovà J, Lowengrub J, Meine H, Moltz JH, Pal C, Piraud M, Qi X, Qi J, Rempfler M, Roth K, Schenk A, Sekuboyina A, Vorontsov E, Zhou P, Hülsemeyer C, Beetz M, Ettlinger F, Gruen F, Kaissis G, Lohöfer F, Braren R, Holch J, Hofmann F, Sommer W, Heinemann V, Jacobs C, Mamani GEH, van Ginneken B, Chartrand G, Tang A, Drozdzal M, Ben-Cohen A, Klang E, Amitai MM, Konen E, Greenspan H, Moreau J, Hostettler A, Soler L, Vivanti R, Szeskin A, Lev-Cohain N, Sosna J, Joskowicz L, Menze BH (2019) The Liver Tumor Segmentation Benchmark (LiTS). arXiv:1901.04056
Dicken V, Hänsch A, Moltz J, Haas B, Coradi T, Morgas T, Klein J (2019) Quantitative and qualitative methods for efficient evaluation of multiple 3D organ segmentations. Proceedings of SPIE Medical Imaging: Image Processing. 1094914:pp 1–8
Moltz JH (2019) Stability of radiomic features of liver lesions from manual delineation in CT scans. Proceedings of SPIE Medical Imaging: Computer-Aided Diagnosis. 109501W:pp 1–7
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


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
Flechsig P, Walker C, Kratochwil C, Konig L, Iagura A, Moltz J, Holland-Letz T, Kauczor H-U, Haberkorn U, Giesel FL (2018) Role of CT Density in PET/CT-Based Assessment of Lymphoma. Mol Imaging Biol 20(4):641–649


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
Flechsig P, Frank P, Kratochwil C, Antoch G, Rath D, Moltz J, Rieser M, Warth A, Kauchzor H-U, Schwartz LH, Haberkorn U, Giesel FL (2017) Radiomic Analysis using Density Threshold for FDG-PET/CT-Based N-Staging in Lung Cancer Patients. Mol Imaging Biol 19(2):315–322
Giesel F, Schneider F, Kratochwil C, Rath D, Holland-Letz T, Moltz J, Kauczor H-U, Schwartz L, Haberkorn U, Flechsig P (2017) Correlation Between SUVmax and CT Radiomic Analysis Using Lymph Node Density in PET/CT-Based Lymph Node Staging. J Nucl Med 58(2):282–287
Vinsensia M, Chyoke PL, Hadaschik B, Holland-Letz T, Moltz J, Kopka K, Rauscher I, Mier W, Schwaiger M, Haberkorn U, Mauer T, Kratochwil C, Eiber M, Giesel FL (2017) (68)Ga-PSMA PET/CT and Volumetric Morphology of PET-Positive Lymph Nodes Stratified by Tumor Differentiation of Prostate Cancer. J Nucl Med 58(12):1949–1955


Athelogou M, Kim HJ, Dima A, Obuchowski N, Peskin A, Gavrielides MA, Petrick N, Saiprasad G, Colditz Colditz D, Beaumont H, Oubel E, Tan Y, Zhao B, Kuhnigk J-M, Moltz JH, Orieux G, Gillies RJ, Gu Y, Mantri N, Goldmacher G, Zhang L, Vega E, Bloom M, Jarecha R, Soza G, Tietjen C, Takeguchi T, Yamagata H, Peterson S, Masoud O, Buckler AJ (2016) Algorithm Variability in the Estimation of Lung Nodule Volume From Phantom CT Scans: Results of the QIBA 3A Public Challenge. Acad Radiol 23(8):940–952
Cieciera M, Kratochwil C, Moltz J, Kauczor H-U, Holland-Letz T, Choyke P, Mier W, Haberkorn U, Giesel FL (2016) Semi-automatic 3D-volumetry of liver metastases from neuroendocrine tumors to improve combination therapy with 177Lu-DOTATOC and 90Y-DOTATOC. Diagn Interv Radiol 22:201–206


Buckler AJ, Danagoulian J, Johnson K, Peskin A, Gavrielides MA, Petrick N, Obuchowski NA, Beaumont H, Hadjiiski L, Jarecha R, Kuhnigk JM, Mantri N, McNitt-Gray M, Moltz JH, Nyiri G, Peterson S, Tervé P, Tietjen C, von L E, Ma X, St P S, Athelogou M (2015) Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data. Acad Radiol 22(11):1393–1408
Dicken V, Bornemann L, Moltz JH, Peitgen H-O, Zaim S, Scheuring U (2015) Comparison of Volumetric and Linear Serial CT Assessments of Lung Metastases in Renal Cell Carcinoma Patients in a Clinical Phase IIB Study. Acad Radiol 22(5):619–625
Giesel FL, Fiedler H, Stefanova M, Sterzing F, Rius M, Kopka K, Moltz JH, Afshar-Oromieh A, Choyke PL, Haberkorn U, Kratochwil C (2015) PSMA PET/CT with Glu-urea-Lys-(Ahx)-[(68)Ga(HBED-CC)] versus 3D CT volumetric lymph node assessment in recurrent prostate cancer. Eur J Nucl Med Mol Imaging 42(12):1794–1800
Weiler F, Chlebus G, Rieder C, Moltz J, Waring A, Brachmann C, Traulsen N, Corr D, Wirtz S, Krass S, Hahn HK (2015) Building Blocks for Clinical Research in Adaptive Radiotherapy. Proc. of CURAC 2015. pp 139–144


Flechsig P, Kratochwil C, Schwartz LH, Rath D, Moltz J, Antoch G, Heussel CP, Rieser M, Warth A, Zabeck H, Kauczor HU, Haberkorn U, Giesel FL (2014) Quantitative Volumetric CT-Histogram Analysis in N-Staging of 18F-FDG-Equivocal Patients with Lung Cancer. J Nucl Med 55(4):559–564
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
Laue HOA, Kohlmann P, Dicken V, Moltz J, Sedlaczek O, Olesch J, Lotz J, Kikinis R, Hahn HK (2014) An application for comparing quantitative DCE- and DWI-MRI with pathology supporting investigators correlating radiology, pathology and tumor biology in lung cancer. Annual Meeting Radiological Society of North America (RSNA). QRR005


Heckel F, Ivanov MI, Moltz JH, Hahn HK (2013) Toward Automated Validation of Sketch-based 3D Segmentation Editing Tools. Proceedings of Scandinavian Conferences on Image Analysis. Lecture Notes in Computer Science, pp 256–265
Heckel F, Moltz JH, Tietjen C, Hahn HK (2013) Sketch-Based Editing Tools for Tumour Segmentation in 3D Medical Images. Comput Graph Forum 32(8):144–157
Moltz JH (2013) Lesion segmentation and tracking for CT-based chemotherapy monitoring. Ph.D. thesis
Moltz JH, Steinberg C, Geisler B, Hahn HK (2013) A tool for efficient creation of probabilistic expert segmentations. Medical Image Understanding and Analysis. pp 7–12
Stoecker C, Welter S, Moltz JH, Lassen B, Kuhnigk JM, Krass S, Peitgen HO (2013) Determination of lung segments in computed tomography images using the Euclidean distance to the pulmonary artery. Med Phys 40(9):091912


Barbieri S, Bauer MHA, Klein J, Moltz J, Nimsky C, Hahn HK (2012) DTI Segmentation via the Combined Analysis of Connectivity Maps and Tensor Distances. Neuroimage 60(2):1025–1035
Giesel FL, Kratochwil C, Mehndiratta A, Wulfert S, Moltz JH, Zechmann CM, Kauczor HU, Haberkorn U, Ley S (2012) Comparison of neuroendocrine tumor detection and characterization using DOTATOC-PET in correlation with contrast enhanced CT and delayed contrast enhanced MRI. Eur J Radiol 81(10):2820–2825
Moltz JH, D'Anastasi M, Kiessling A, Pinto dos Santos D, Schulke C, Peitgen HO (2012) Workflow-centred evaluation of an automatic lesion tracking software for chemotherapy monitoring by CT. Eur Radiol 22(12):2759–2767
Wang L, Moltz JH, Bornemann L, Hahn HK (2012) A Minimally-interactive Method to Segment Enlarged Lymph Nodes in 3D Thoracic CT Images Using a Rotatable Spiral-Scanning Technique. Proc. SPIE Medical Imaging. 83150D:pp 1–8


Moltz JH, Rühaak J, Hahn HK, Peitgen H-O (2011) A Novel Adaptive Scoring System for Segmentation Validation with Multiple Reference Masks. Proc SPIE Medical Imaging. 796214:pp 1–10
Moltz JH, Braunewell S, Rühaak J, Heckel F, Barbieri S, Tautz L, Hahn HK, Peitgen H-O (2011) Analysis of Variability in Manual Liver Tumor Delineation in CT Scans. IEEE International Symposium on Biomedical Imaging. pp 1974–1977
Schwier M, Moltz JH, Peitgen H-O (2011) Object-based analysis of CT images for automatic detection and segmentation of hypodense liver lesions. Int J CARS 6(6):737–747


Schumann C, Rieder C, Bieberstein J, Weihusen A, Zidowitz S, Moltz JH, Preusser T (2010) State of the Art in Computer-Assisted Planning, Intervention and Assessment of Liver Tumor Ablation. Crit Rev Biomed Eng 38(1):31–52


Heckel F, Moltz JH, Bornemann L, Dicken V, Bauknecht HC, Fabel M, Hittinger M, Kießling A, Meier S, Püsken M, Peitgen H-O (2009) 3D contour based local manual correction of tumor segmentations in CT scans. Proceedings of SPIE Medical Imaging. 72593L:pp 1–9
Heckel F, Moltz JH, Dicken V, Geisler B, Bauknecht HC, Fabel M, Meier S, Peitgen H-O (2009) 3D contour based local manual correction of liver segmentations in CT scans. Proceedings of Computer Assisted Radiology and Surgery. pp 45–46
Moltz JH, Bornemann L, Kuhnigk JM, Dicken V, Peitgen E, Meier S, Bolte H, Fabel M, Bauknecht HC, Hittinger M, Kießling A, Püsken M, Peitgen H-O (2009) Advanced Segmentation Techniques for Lung Nodules, Liver Metastases, and Enlarged Lymph Nodes in CT Scans. IEEE J Sel Topics Signal Proc 3(1):122–134
Moltz JH, Geisler B, Bornemann L, Weihusen A, Peitgen H-O (2009) Segmentation of Thermal Liver Lesions for CT-Based Radiofrequency Ablation Assessment. Proceedings ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing. pp 19–24
Moltz JH, Schwier M, Peitgen H-O (2009) A General Framework for Automatic Detection of Matching Lesions in Follow-up CT. IEEE International Symposium on Biomedical Imaging. pp 843–846
Reeves AP, Jirapatnakul AC, Biancardi AM, Apanasovich TV, Moltz JH, Kuhnigk JM (2009) The VOLCANO´09 Challenge: Preliminary Results. Proceedings of the Second International Workshop on Pulmonary Image Analysis. pp 353–364


Moltz JH, Bornemann L, Dicken V, Peitgen H-O (2008) Segmentation of Liver Metastases by Adaptive Thresholding and Morphological Processing. The MIDAS Journal – Grand Challenge Liver Tumor Segmentation (2008 MICCAI Workshop)
Moltz JH, Kuhnigk J-M, Bornemann L, Peitgen H-O (2008) Segmentation of Juxtapleural Lung Nodules in CT Scans Based on Ellipsoid Approximation. Proceeding First International Workshop on Pulmonary Image Analysis. pp 25–32
Moltz JH, Kuhnigk J-M, Bornemann L, Peitgen H-O (2008) Segmentierung pleuraständiger Lungenrundherde in CT-Bildern mittels Ellipsoidapproximation. In: Tolxdorff T, Braun J, Deserno TM, Handels H, Horsch A, Meinzer H-P (eds) Bildverarbeitung für die Medizin. Springer-Verlag, Berlin, Heidelberg, pp 173–177