Menze, Bjoern

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 6,781

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · Apollo - University of Cambridge Repository

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge

Bakas, S., Reyes, M., Jakab, A., Bauer, S., Rempfler, M., Crimi, A., Shinohara, R. T., Berger, C., Ha, S. M., Rozycki, M., et al. (2018) · arXiv

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 1,441

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 1,384

Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

Christ, P. F., Elshaer, M. E. A., Ettlinger, F., Tatavarty, S., Bickel, M., Bilic, P., Rempfler, M., Armbruster, M., Hofmann, F., D’Anastasi, M., et al. (2016) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 625

Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge

Campello, V. M., Gkontra, P., Izquierdo, C., Martin-Isla, C., Sojoudi, A., Full, P. M., Maier-Hein, K., Zhang, Y., He, Z., Ma, J., et al. (2021) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesCardiac Imaging and Diagnostics

Cited by 481

Panoptic imaging of transparent mice reveals whole-body neuronal projections and skull–meninges connections

Cai, R., Pan, C., Ghasemigharagoz, A., Todorov, M. I., Förstera, B., Zhao, S., Bhatia, H. S., Parra-Damas, A., Mrowka, L., Theodorou, D., et al. (2019) · Nature Neuroscience

Advanced Fluorescence Microscopy TechniquesCell Image Analysis Techniques

Cited by 470

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

Machine learning analysis of whole mouse brain vasculature

Todorov, M. I., Paetzold, J. C., Schoppe, O., Tetteh, G., Shit, S., Efremov, V., Todorov-Völgyi, K., Düring, M., Dichgans, M., Piraud, M., et al. (2020) · Nature Methods

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 338

Cellular and Molecular Probing of Intact Human Organs

Zhao, S., Todorov, M. I., Cai, R., -Maskari, R. A., Steinke, H., Kemter, E., Mai, H., Rong, Z., Warmer, M., Stanic, K., et al. (2020) · Cell

Advanced Fluorescence Microscopy TechniquesSingle-cell and spatial transcriptomics

Cited by 292

Understanding metric-related pitfalls in image analysis validation

Reinke, A., Tizabi, M. D., Baumgartner, M., Eisenmann, M., Heckmann-Nötzel, D., Kavur, A. E., Rädsch, T., Sudre, C. H., Acion, L., Antonelli, M., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 241

Deep Learning Reveals Cancer Metastasis and Therapeutic Antibody Targeting in the Entire Body

Pan, C., Schoppe, O., Parra-Damas, A., Cai, R., Todorov, M. I., Gondi, G., von Neubeck, B., Böğürcü-Seidel, N., Seidel, S., Sleiman, K., et al. (2019) · Cell

Cell Image Analysis TechniquesAI in cancer detection

Cited by 206

Spatial proteomics in three-dimensional intact specimens

Bhatia, H. S., Brunner, A.-D., Öztürk, F., Kapoor, S., Rong, Z., Mai, H., Thielert, M., Ali, M., Al-Maskari, R., Paetzold, J. C., et al. (2022) · Cell

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 129

Common Limitations of Image Processing Metrics: A Picture Story

Reinke, A., Tizabi, M. D., Sudre, C. H., Eisenmann, M., Rädsch, T., Baumgartner, M., Acion, L., Antonelli, M., Arbel, T., Bakas, S., et al. (2021) · arXiv

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 126

Local Structure Prediction with Convolutional Neural Networks for Multimodal Brain Tumor Segmentation

Dvořák, P., & Menze, B. (2016) · Lecture Notes in Computer Science

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 119

Deep learning-enabled multi-organ segmentation in whole-body mouse scans

Schoppe, O., Pan, C., Coronel, J., Mai, H., Rong, Z., Todorov, M. I., Müskes, A., Navarro, F., Li, H., Ertürk, A., et al. (2020) · Nature Communications

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 104

clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

Shit, S., Paetzold, J. C., Sekuboyina, A., Ezhov, I., Unger, A., Zhylka, A., Pluim, J. P. W., Bauer, U., & Menze, B. H. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 60

Metrics reloaded: Recommendations for image analysis validation

Maier-Hein, L., Reinke, A., Godau, P., Tizabi, M. D., Buettner, F., Christodoulou, E., Glocker, B., Isensee, F., Kleesiek, J., Kozubek, M., et al. (2022) · arXiv

Cell Image Analysis TechniquesMedical Image Segmentation Techniques

Cited by 59

The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor research

Pati, S., Baid, U., Edwards, B., Sheller, M. J., Foley, P., Anthony Reina, G., Thakur, S., Sako, C., Bilello, M., Davatzikos, C., et al. (2022) · Physics in Medicine & Biology

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 51

CT2Rep: Automated Radiology Report Generation for 3D Medical Imaging

Hamamci, I. E., Er, S., & Menze, B. (2024) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 47

Virtual reality-empowered deep-learning analysis of brain cells

Kaltenecker, D., Al-Maskari, R., Negwer, M., Hoeher, L., Kofler, F., Zhao, S., Todorov, M., Rong, Z., Paetzold, J. C., Wiestler, B., et al. (2024) · Nature Methods

Cell Image Analysis TechniquesSingle-cell and spatial transcriptomics

Cited by 38

vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation

Wittmann, B., Wattenberg, Y., Amiranashvili, T., Shit, S., & Menze, B. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Medical Image Segmentation TechniquesDomain Adaptation and Few-Shot Learning

Cited by 25