# Bram van Ginneken

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/bram-van-ginneken/

## Facts

| Field | Value |
| --- | --- |
| Citations | 71,094 |
| Field | Radiomics and Machine Learning in Medical Imaging |
| h-index | 107 |
| i10-index | 402 |
| Last Known Institution | Radboud University Nijmegen |
| OpenAlex ID | https://openalex.org/A5042982766 |
| ORCID iD | https://orcid.org/0000-0003-2028-8972 |
| Works | 716 |

## Researcher papers

- [Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets](https://scholariq.org/papers/comparison-and-evaluation-of-methods-for-liver-segmentation-from-ct-datasets/)
- [From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge](https://scholariq.org/papers/from-detection-of-individual-metastases-to-classification-of-lymph-node-status/)
- [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/)
- [Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies](https://scholariq.org/papers/using-deep-convolutional-neural-networks-to-identify-and-classify-tumor/)
- [Understanding metric-related pitfalls in image analysis validation](https://scholariq.org/papers/understanding-metric-related-pitfalls-in-image-analysis-validation/)

## Researcher topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)

## Researcher university

- [Radboud University Nijmegen](https://scholariq.org/institutions/radboud-university-nijmegen/)

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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.