Müller, Henning

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Zwanenburg, A., Vallières, M., Abdalah, M. A., Aerts, H. J. W. L., Andrearczyk, V., Apte, A., Ashrafinia, S., Bakas, S., Beukinga, R. J., Boellaard, R., et al. (2020) · Radiology

Radiomics and Machine Learning in Medical ImagingImage Retrieval and Classification Techniques

Cited by 4,177

Deep learning with convolutional neural networks applied to electromyography data: a resource for the classification of movements for prosthetic hands

Atzori, M., Cognolato, M., & Müller, H. (2016) · Frontiers in Neurorobotics

Muscle activation and electromyography studiesEEG and Brain-Computer Interfaces

Cited by 684

CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Kocak, B., Baessler, B., Bakas, S., Cuocolo, R., Fedorov, A., Maier-Hein, L., Mercaldo, N., Müller, H., Orlhac, F., Pinto dos Santos, D., et al. (2023) · Insights into Imaging

Radiomics and Machine Learning in Medical ImagingRadiology practices and education

Cited by 471

Building a reference multimedia database for interstitial lung diseases

Depeursinge, A., Vargas, A., Platon, A., Geissbuhler, A., Poletti, P.-A., & Müller, H. (2012) · Computerized Medical Imaging and Graphics

Interstitial Lung Diseases and Idiopathic Pulmonary FibrosisRadiomics and Machine Learning in Medical Imaging

Cited by 248

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

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

Assessment of Internet-based tele-medicine in Africa (the RAFT project)

Bagayoko, C. O., Müller, H., & Geissbuhler, A. (2006) · Computerized Medical Imaging and Graphics

Telemedicine and Telehealth ImplementationICT in Developing Communities

Cited by 69

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

Not so weak PICO: leveraging weak supervision for participants, interventions, and outcomes recognition for systematic review automation.

Dhrangadhariya, A., & Müller, H. (2023) · JAMIA Open

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 18

BIAS: Transparent reporting of biomedical image analysis challenges

Maier-Hein, L., Reinke, A., Kozubek, M., Martel, A. L., Arbel, T., Eisenmann, M., Hanbury, A., Jannin, P., Müller, H., Onogur, S., et al. (2020) · Medical Image Analysis

Medical Image Segmentation TechniquesCell Image Analysis Techniques

Cited by 9

Distant-cto: a zero cost, distantly supervised approach to improve low-resource entity extraction using clinical trials literature.

Dhrangadhariya, A., & Müller, H. (2022) · Proceedings of the 21st Workshop on Biomedical Language Processing

Biomedical Text Mining and OntologiesTopic Modeling

Cited by 3