# Klaus Maier‐Hein

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/klaus-maier-hein/

## Facts

| Field | Value |
| --- | --- |
| Citations | 29,196 |
| Field | Radiomics and Machine Learning in Medical Imaging |
| h-index | 67 |
| i10-index | 211 |
| Last Known Institution | German Cancer Research Center |
| OpenAlex ID | https://openalex.org/A5027292126 |
| ORCID iD | https://orcid.org/0000-0002-6626-2463 |
| Works | 509 |

## Researcher papers

- [The challenge of mapping the human connectome based on diffusion tractography](https://scholariq.org/papers/the-challenge-of-mapping-the-human-connectome-based-on-diffusion-tractography/)
- [ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI](https://scholariq.org/papers/isles-2015-a-public-evaluation-benchmark-for-ischemic-stroke-lesion-segmentation/)
- [Metrics reloaded: recommendations for image analysis validation](https://scholariq.org/papers/metrics-reloaded-recommendations-for-image-analysis-validation/)
- [Why rankings of biomedical image analysis competitions should be interpreted with care](https://scholariq.org/papers/why-rankings-of-biomedical-image-analysis-competitions-should-be-interpreted/)
- [Federated learning enables big data for rare cancer boundary detection](https://scholariq.org/papers/federated-learning-enables-big-data-for-rare-cancer-boundary-detection/)
- [Understanding metric-related pitfalls in image analysis validation](https://scholariq.org/papers/understanding-metric-related-pitfalls-in-image-analysis-validation/)
- [Framework and baseline examination of the German National Cohort (NAKO)](https://scholariq.org/papers/framework-and-baseline-examination-of-the-german-national-cohort-nako/)

## Researcher topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Advanced Neuroimaging Techniques and Applications](https://scholariq.org/topics/advanced-neuroimaging-techniques-and-applications/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Researcher university

- [German Cancer Research Center](https://scholariq.org/institutions/german-cancer-research-center/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.