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Brain Tumor Cell Density Estimation from Multi-modal MR Images Based on a Synthetic Tumor Growth Model.

E. Geremia, B. Menze, M. Prastawa, M. Weber, A. Criminisi, and N. Ayache. MCV, volume 7766 of Lecture Notes in Computer Science, page 273-282. Springer, (2012)

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Univ. -Prof. Dr. -Ing. Marc-André Keip University of Stuttgart

André Jaquemod University of Stuttgart

Univ. -Prof. Dr. rer. nat. André Thess University of Stuttgart

Dr. -Ing. André Buchau University of Stuttgart

André Weiß University of Stuttgart

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Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions.L. Maier-Hein, M. Eisenmann, A. Reinke, S. Onogur, M. Stankovic, P. Scholz, T. Arbel, H. Bogunovic, A. Bradley, A. Carass and 28 other author(s). CoRR, (2018)Research and applications: Three-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images.A. Neubert, J. Fripp, C. Engstrom, D. Walker, M. Weber, R. Schwarz, and S. Crozier. JAMIA, 20 (6): 1082-1090 (2013)Bringing the Algorithms to the Data: Cloud-Based Benchmarking for Medical Image Analysis.A. Hanbury, H. Müller, G. Langs, M. Weber, B. Menze, and T. Fernandez. CLEF, volume 7488 of Lecture Notes in Computer Science, page 24-29. Springer, (2012)Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.S. Bakas, M. Reyes, A. Jakab, S. Bauer, M. Rempfler, A. Crimi, R. Shinohara, C. Berger, S. Ha, M. Rozycki and 41 other author(s). CoRR, (2018)Detecting Bone Lesions in Multiple Myeloma Patients Using Transfer Learning.M. Perkonigg, J. Hofmanninger, B. Menze, M. Weber, and G. Langs. DATRA/PIPPI@MICCAI, volume 11076 of Lecture Notes in Computer Science, page 22-30. Springer, (2018)The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS).B. Menze, A. Jakab, S. Bauer, J. Kalpathy-Cramer, K. Farahani, J. Kirby, Y. Burren, N. Porz, J. Slotboom, R. Wiest and 58 other author(s). IEEE Trans. Medical Imaging, 34 (10): 1993-2024 (2015)QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.R. Mehta, A. Filos, U. Baid, C. Sako, R. McKinley, M. Rebsamen, K. Dätwyler, R. Meier, P. Radojewski, G. Murugesan and 82 other author(s). CoRR, (2021)Creating a Large-Scale Silver Corpus from Multiple Algorithmic Segmentations.M. Krenn, M. Dorfer, O. del Toro, H. Müller, B. Menze, M. Weber, A. Hanbury, and G. Langs. MCV@MICCAI, volume 9601 of Lecture Notes in Computer Science, page 103-115. Springer, (2015)Cloud-Based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks.O. del Toro, H. Müller, M. Krenn, K. Gruenberg, A. Taha, M. Winterstein, I. Eggel, A. Foncubierta-Rodríguez, O. Goksel, A. Jakab and 19 other author(s). IEEE Trans. Med. Imaging, 35 (11): 2459-2475 (2016)A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation - With Application to Tumor and Stroke.B. Menze, K. Leemput, D. Lashkari, T. Riklin-Raviv, E. Geremia, E. Alberts, P. Gruber, S. Wegener, M. Weber, G. Székely and 2 other author(s). IEEE Trans. Med. Imaging, 35 (4): 933-946 (2016)