# Detection and classification of contrast‐enhancing masses by a fully automatic computer‐assisted diagnosis system for breast MRI

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/detection-and-classification-of-contrast-enhancing-masses-by-a-fully-automatic/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Diane M. Renz,Joachim Böttcher,Felix Diekmann,Alexander Poellinger,Martin Maurer,Alexander Pfeil,Florian Streitparth,Federico Collettini,Ulrich Bick,Bernd Hamm,Eva Maria Fallenberg |
| Citations | 54 |
| DOI | 10.1002/jmri.23516 |
| Fields | Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/jmri.23516 |
| OpenAlex ID | https://openalex.org/W2091676557 |
| PMID | 22247104 |
| Type | article |
| Year | 2012 |

## Paper authors

- [Diane M. Renz](https://scholariq.org/researchers/diane-m-renz/)

## Paper primary topic

- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)

## Paper topics

- [MRI in cancer diagnosis](https://scholariq.org/topics/mri-in-cancer-diagnosis/)
- [Breast Lesions and Carcinomas](https://scholariq.org/topics/breast-lesions-and-carcinomas/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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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.