From the 1 of 5 papers with an AI index.
12 citations
- Heidelberg UniversityDE5 papers
- University Hospital HeidelbergDE3 papers
- Harvard UniversityUS2 papers
- Helmholtz MunichDE2 papers
- University of ZurichCH2 papers
- Abterra Biosciences (United States)US1 paper
- AGH University of KrakowPL1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
- Beijing Academy of Artificial IntelligenceCN1 paper
- Brigham and Women's HospitalUS1 paper
- Canon (United States)US1 paper
- Center for Excellence in Brain Science and Intelligence TechnologyCN1 paper
5 papers
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…
Tests for categorical data beyond Pearson: A distance covariance and energy distance approach
Fernando Castro-Prado, Wenceslao González-Manteiga, Javier Costas +2
Categorical variables are of uttermost importance in biomedical research. When two of them are considered, it is often the case that one wants to test whether or not they are stati…
Direct optimization of the probability of lesion origin in proton treatment planning for low-grade glioma patients
Tim Ortkamp, Habiba Sallem, Semi Harrabi +4
In proton therapy of low-grade glioma (LGG) patients, contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging are considered predictive of late radiation-induced les…
Design for a Digital Twin in Clinical Patient Care
Anna-Katharina Nitschke, Carlos Brandl, Fabian Egersdörfer +3
Digital Twins hold great potential to personalize clinical patient care, provided the concept is translated to meet specific requirements emerging from established clinical workflo…
In search of truth: Evaluating concordance of AI-based anatomy segmentation models
Lena Giebeler, Deepa Krishnaswamy, David Clunie +9
Purpose AI-based methods for anatomy segmentation can help automate characterization of large imaging datasets. The growing number of similar in functionality models raises the cha…