Google Scholar : my papers gathered over 3200 citations and I have an h-index of 18.

Preprints

  • MISATO - Machine learning dataset of protein-ligand complexes for structure-based drug discovery, T. Siebenmorgen, F. Menezes, S. Benassou, E. Merdivan, S. Kesselheim, M. Piraud, F. J. Theis, M. Sattler, G. M. Popowicz, submitted (bioRxiv).
  • Panoptica--instance-wise evaluation of 3D semantic and instance segmentation maps, F. Kofler, H. Möller, J. A. Buchner, E. de la Rosa, I. Ezhov, M. Rosier, I. Mekki, S. Shit, M. Negwer, R. Al-Maskari, A. Ertürk, S. Vinayahalingam, F. Isensee, S. Pati, D. Rueckert, J. S. Kirschke, S. K. Ehrlich, A. Reinke, B. Menze, B. Wiestler, M. Piraud, submitted (arXiv).
  • Framing image registration as a landmark detection problem for better representation of clinical relevance, D. Waldmannstetter, B. Wiestler, J. Schwarting, I. Ezhov, M. Metz, S. Bakas, B. Baheti, S. Chakrabarty, J. S. Kirschke, R. A. Heckemann, M. Piraud, F. Kofler, B. Menze, submitted (arXiv).
  • Primitive Simultaneous Optimization of Similarity Metrics for Image Registration, D. Waldmannstetter, B. Wiestler, J. Schwarting, I. Ezhov, M. Metz, S. Bakas, B. Baheti, S. Chakrabarty, D. Rueckert, J. S. Kirschke, R. A. Heckemann, M. Piraud, B. Menze, F. Kofler, submitted (arXiv).
  • Probe set selection for targeted spatial transcriptomics, L. B. Kuemmerle, M. D. Luecken, A. B. Firsova, L. Barros de Andrade e Sousa, L. Straßer, L. Heumos, I. I. Mekki, K. T. Mahbubani, A. Sountoulidis, T. Balassa, F. Kovacs, P. Horvath, M. Piraud, A. Ertürk, C. Samakovlis, F. J. Theis, submitted (bioRxiv).
  • Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings, F. Kofler, I. Ezhov, L. Fidon, I. Horvath, E. de la Rosa, J. LaMaster, H. Li, T. Finck, S. Shit, J. Paetzold, S. Bakas, M. Piraud, J. Kirschke, T. Vercauteren, C. Zimmer, B. Wiestler, B. Menze, submitted (arXiv).
  • Improved prediction of bacterial CRISPRi guide efficiency through data integration and automated machine learning, Y. Yu, S. Gawlitt, L. Barros de Andrade e Sousa, E. Merdivan, M. Piraud, C. Beisel, Lars Barquist, submitted (bioRxiv).
  • Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations, S. Shit, I. Ezhov, L. Mächler, J. Lipkova, J. C. Paetzold, F. Kofler, M. Piraud, B. H. Menze, submitted (arXiv).

    • Published papers

  • Reporting electricity consumption is essential for sustainable AI, C. Debus, M. Piraud, A. Streit, F. Theis, M. Götz, Nature Machine Intelligence, vol 5, 2023.
  • Providing AI expertise as an infrastructure in academia, M. Piraud, A. Camero, M. Götz, S. Kesselheim, P. Steinbach, T. Weigel, Patterns, vol 4, 2023.
  • Approaching Peak Ground Truth, F. Kofler, J. Wahle, I. Ezhov, S. Wagner, R. Al-Maskari, E. Gryska, M. Todorov, C. Bukas, F. Meissen, T. Peng, A. Ertürk, D. Rückert, R. Heckemann, J. Kirschke, C. Zimmer, B. Wiestler, B. Menze, M. Piraud, 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023.
  • Echo2Pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice, C. Bukas, I. Galter, P. da Silva-Buttkus, H. Fuchs, H. Maier, V. Gailus-Durner, C. L. Müller, M. Hrabĕ; de Angelis, M. Piraud, N. Spielmann, Mammalian Genome, vol 34, 2023.
  • blob loss: instance imbalance aware loss functions for semantic segmentation, F. Kofler, S. Shit, I. Ezhov, L. Fidon, I. Horvath, R. Al-Maskari, H. Li, H. Bhatia, T. Loehr, M. Piraud, A. Ertürk, J. Kirschke, J. Peeken, T. Vercauteren, C. Zimmer, B. Wiestler, B. Menze, International Conference on Information Processing in Medical Imaging (IPMI). Cham: Springer Nature Switzerland, 2023.
  • Genetically encoded barcodes for correlative volume electron microscopy, F. Sigmund, et al., Nature Biotechnology, 2023.
  • Whole-body cellular mapping in mouse using standard IgG antibodies, H. Mai, et al., Nature Biotechnology, 2023.
  • Identifying core MRI sequences for reliable automatic brain metastasis segmentation, J. A. Buchner, et al., Radiotherapy and Oncology, vol 188, 2023.
  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge, S. Bakas, et al., Medical Image Analysis, vol 84, 2023.
  • The Liver Tumor Segmentation Benchmark (LiTS), P. Bilic, et al., Medical Image Analysis , 2023.
  • Formate promotes invasion and metastasis in reliance on lipid metabolism, C. Delbrouck, et al., Cell Reports, vol 42, 2023.
  • Introduction to AI and its medical applications: Crash Course for an audience with diverse scientific backgrounds, D. Cea, H. Hoffmann, M. Piraud, ECML: European Conference on Machine Learning, Teaching Machine Learning Workshop, 2022.
  • A hybrid radiomics approach to modeling progression-free survival in head and neck cancers, S. Starke, D. Thalmeier, P. Steinbach, M. Piraud, 3D Head and Neck Tumor Segmentation in PET/CT Challenge. Cham: Springer International Publishing, 2021.
  • Patient-specific virtual spine straightening and vertebra inpainting: An automatic framework for osteoplasty planning, C. Bukas, B. Jian, L. F. Rodriguez Venegas, F. De Benetti, S. Ruehling, A. Sekuboyina, J. Gempt, J. S. Kirschke, M. Piraud, J. Oberreuter, N. Navab, T. Wendler, Medical Image Computing and Computer Assisted Intervention - MICCAI 2021, Proceedings, Springer International Publishing, 2021.
  • DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes, G. Tetteh, V. Efremov, N. D. Forkert, M. Schneider, J. Kirschke, B. Weber, C. Zimmer, M. Piraud, B. H. Menze, Frontiers in Neuroscience, 2020.
  • Reliable Saliency Maps for Weakly-Supervised Localization of Disease Patterns, M. Möller, M. Kohl, S. Braunewell, F. Kofler, B. Wiestler, J. S. Kirschke, B. H. Menze, M. Piraud, Interpretable and Annotation-Efficient Learning for Medical Image Computing: Third International Workshop, iMIMIC 2020, Held in Conjunction with MICCAI 2020, Proceedings, Springer International Publishing, 2020.
  • Automated analysis of whole brain vasculature using machine learning, M. I. Todorov, J. C. Paetzold, O. Schoppe, G. Tetteh, V. Efremov, K. Völgyi, M. Düring, M. Dichgans, M. Piraud, B. Menze, A. Ertürk, Nature Methods, 2020.
  • Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee, S. Shit, A. Ravi, I. Ezhov, J. Lipkova, M. Piraud, B. Menze, NeurIPS: Conference on Neural Information Processing Systems, Machine Learning with Guarantees Workshop, 2019.
  • Towards Quantitative Imaging Biomarkers of Tumor Dissemination: a Multi-scale Parametric Modeling of Multiple Myeloma, M. Piraud, M. Wennmann, L. Kintzelé, J. Hillengass, U. Keller, G. Langs, M.-A. Weber, B. H. Menze, Medical Image Analysis, vol 57, 2019.
  • Long Short Term Memory Recurrent Neural Network for MR Fingerprinting parameter estimation, N. Andriamanga, C. M. Pirkl, A. Sekuboyina, G. Buonincontri, M. I. Menzel, P. A. Gómez, M. Piraud , B. H. Menze, ESMRMB 2019, 36th Annual Scientific Meeting, 2019.
  • Asymmetric Cascade Networks for Focal Bone Lesion Prediction in Multiple Myeloma, R. Licandro, J. Hofmanninger, M. Perkonigg, S. Röhrich, M.-A. Weber, M. Wennmann, L. Kintzele, M. Piraud, B. Menze, G. Langs, MIDL: The Medical Imaging with Deep Learning conference, 2019.
  • Knowledge-aided Convolutional Neural Networks for Small Organ Segmentation, Y. Zhao, H. Li, S. Wan, A. Sekuboyina, X. Hu, G. Tetteh, M. Piraud, B. H. Menze, IEEE J Biomed Health Inform, 2019.
  • Multi-level Activation for Segmentation of Hierarchically-nested Classes, M. Piraud, A. Sekuboyina and B. H. Menze, ECCV 2018 Workshops. Lecture Notes in Computer Science, vol 11134, 2019.
  • Hierarchal multi-class segmentation of glioma using networks with multi-level activation function, X. Hu, H. Li, Y. Zhao, C. Dong, B. H. Menze, and M. Piraud, BrainLes 2018. Lecture Notes in Computer Science, vol 11384, 2019.
  • Volumetry based biomarker speed of growth: Quantifying the change of total tumor volume in whole-body magnetic resonance imaging over time improves risk stratification of smoldering multiple myeloma patients, M. Wennmann, L. Kintzelé, M. Piraud, B. H. Menze, T. Hielscher, J. Hofmanninger, B. Wagner, H.-U. Kauczor, M. Merz, J. Hillengass, G. Langs and M.-A. Weber, Oncotarget, 9 25254, 2018.
  • Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on 68Ga-Pentixafor PET/CT Imaging Using Deep Learning Methods, L. Xu, G. Tetteh, J. Lipkova, Y. Zhao, H. Li, P. Christ, M. Piraud, A. Buck, K. Shi and B. Menze, Contrast Media & Molecular Imaging 2018, 2391925, 2018.
  • W-Net for Whole-Body Bone Lesion Detection of Multiple Myeloma Patients on 68Ga-Pentixafor PET/CT Imaging, L. Xu, G. Tetteh, M. Mustafa, J. Lipkova, Y. Zhao, M. Bieth, P. Christ, M. Piraud, B. Menze and K. Shi, CMMI/RAMBO/SWITCH 2017, LNCS 10555, pp. 23-30, 2017.
  • Precursor of Laughlin state of hard core bosons on a two leg ladder, A. Petrescu, M. Piraud, G. Roux, I. P. McCulloch and K. Le Hur, Phys. Rev. B, 96 014524, 2017.
  • Symmetry-broken states in a system of interacting bosons on a two-leg ladder with a uniform Abelian gauge field, S. Greschner, M. Piraud, F. Heidrich-Meisner, I. P. McCulloch, U. Schollwöck, and T. Vekua, Phys. Rev. A, 94 063628, 2016.
  • Spontaneous Increase of Magnetic Flux and Chiral-Current Reversal in Bosonic Ladders: Swimming against the Tide, S. Greschner, M. Piraud, F. Heidrich-Meisner, I. P. McCulloch, U. Schollwöck, and T. Vekua, Phys. Rev. Lett., 115 190402, 2015.
  • Strongly interacting bosons on a three-leg ladder in the presence of a homogeneous flux, F. Kolley, M. Piraud, I. P. McCulloch, U. Schollwöck, and F. Heidrich-Meisner, New J. Phys., 17 092001, 2015.
  • Vortex and Meissner phases of strongly-interacting bosons on a two-leg ladder, M. Piraud, F. Heidrich-Meisner, I. P. McCulloch, S. Greschner, T. Vekua, and U. Schollwöck, Phys. Rev. B, 91 140406(R), 2015.
  • Anderson Localization of Matter Waves in 3D Anisotropic Disordered Potentials, M. Piraud, L. Sanchez-Palencia and B. Van Tiggelen, Phys. Rev. A, 90 063639, 2014.
  • Quantum magnetism of bosons with synthetic gauge fields in one-dimensional optical lattices: A density-matrix renormalization-group study, M. Piraud, Z. Cai, I. P. McCulloch, and U. Schollwöck, Phys. Rev. A, 89 063618, 2014.
  • Effects of Interactions and Temperature in Disordered Ultra-Cold Bose Gases, C. Adolphs, J. Towers, M. Piraud, K. V. Krutitsky and D. A. W. Hutchinson, J. Mod. Phys., 5 661-672, 2014.
  • Quantum transport of atomic matterwaves in anisotropic 2D and 3D disorder, M. Piraud, L. Pezzé and L. Sanchez-Palencia, New J. Phys., 15 075007, 2013.
  • Tailoring Anderson localization by disorder correlations in 1D speckle potentials, M. Piraud and L. Sanchez-Palencia, Eur. Phys. J. Special topics, 217 91, 2013.
  • Matter wave transport and Anderson localization in anisotropic three-dimensional disorder, M. Piraud, L. Pezzé and L. Sanchez-Palencia, Europhys. Lett., 99 50003, 2012.
  • Anderson localization of matter waves in tailored disordered potentials, M. Piraud, A. Aspect and L. Sanchez-Palencia, Phys. Rev. A, 85 063611, 2012.
  • Three-dimensional localization of ultracold atoms in an optical disordered potential, F. Jendrzejewski, A. Bernard, K. Mueller, P. Cheinet, V. Josse, M. Piraud, L. Pezzé, L. Sanchez-Palencia, A. Aspect and P. Bouyer, Nature Phys., 8 398 , 2012.
  • Localization of a matter wave packet in a disordered potential, M. Piraud, P. Lugan, P. Bouyer, A. Aspect and L. Sanchez-Palencia, Phys. Rev. A, 83 031603(R), 2011.