Search Results for author: Nikolas Lessmann

Found 11 papers, 3 papers with code

Random smooth gray value transformations for cross modality learning with gray value invariant networks

1 code implementation MIDL 2019 Nikolas Lessmann, Bram van Ginneken

Random transformations are commonly used for augmentation of the training data with the goal of reducing the uniformity of the training samples.

Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT

no code implementations12 Feb 2019 Bob D. de Vos, Jelmer M. Wolterink, Tim Leiner, Pim A. de Jong, Nikolas Lessmann, Ivana Isgum

To meet demands of the increasing interest in quantification of CAC, i. e. coronary calcium scoring, especially as an unrequested finding for screening and research, automatic methods have been proposed.

Iterative fully convolutional neural networks for automatic vertebra segmentation and identification

1 code implementation12 Apr 2018 Nikolas Lessmann, Bram van Ginneken, Pim A. de Jong, Ivana Išgum

Precise segmentation and anatomical identification of the vertebrae provides the basis for automatic analysis of the spine, such as detection of vertebral compression fractures or other abnormalities.

Instance Segmentation Semantic Segmentation

Direct and Real-Time Cardiovascular Risk Prediction

no code implementations8 Dec 2017 Bob D. de Vos, Nikolas Lessmann, Pim A. de Jong, Max A. Viergever, Ivana Isgum

The results demonstrate that real-time quantification of CAC burden in chest CT without the need for segmentation of CAC is possible.

Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions

no code implementations1 Nov 2017 Nikolas Lessmann, Bram van Ginneken, Majd Zreik, Pim A. de Jong, Bob D. de Vos, Max A. Viergever, Ivana Išgum

On soft filter reconstructions, the method achieved F1 scores of 0. 89, 0. 89, 0. 67, and 0. 55 for coronary artery, thoracic aorta, aortic valve and mitral valve calcifications, respectively.

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