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Lena Maier-Hein

Researcher at German Cancer Research Center

Publications -  333
Citations -  8361

Lena Maier-Hein is an academic researcher from German Cancer Research Center. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 36, co-authored 273 publications receiving 5637 citations. Previous affiliations of Lena Maier-Hein include Heidelberg University & Karlsruhe Institute of Technology.

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

TL;DR: The CheckList for EvaluAtion of Radiomics research (CLEAR) as mentioned in this paper is a documentation standard for radiomics research that can guide authors and reviewers to improve the quality and reliability and, in turn, the reproducibility of radiomic research.
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Photoacoustics can image spreading depolarization deep in gyrencephalic brain.

TL;DR: In this article, a hybrid photoacoustic and ultrasonic imaging system was used to study spreading depolarization (SD) and its hemodynamics deep in the gyrencephalic brain with high spatiotemporal resolution.
Journal ArticleDOI

Towards a mixed reality environment for preoperative planning of cardiac surgery

TL;DR: A novel approach to studying physical heart models by coupling them with virtual 3D representations in a mixed reality environment which enables cardiac surgeons to interactively trace the mitral annulus, a part of the cardiac skeleton playing a vital role in mitral valve surgery.
Posted Content

BIAS: Transparent reporting of biomedical image analysis challenges

TL;DR: The Biomedical I mage Analysis ChallengeS (BIAS) initiative developed a set of recommendations for the reporting of challenges as discussed by the authors, which aims to improve the transparency of reporting of a biomedical image analysis challenge regardless of field of application, image modality or task category assessed.
Posted Content

What does it all mean? Capturing Semantics of Surgical Data and Algorithms with Ontologies.

TL;DR: It is proposed the establishment of a new ontology for data and algorithms in surgical data science, which can be used to provide common data sets for the community, encouraging sharing of knowledge and comparison of algorithms on common data.