Nikolas Leßmann
Orcid: 0000-0001-7935-9611
According to our database1,
Nikolas Leßmann
authored at least 30 papers
between 2012 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Improving assessment of lesions in longitudinal CT scans: a bi-institutional reader study on an AI-assisted registration and volumetric segmentation workflow.
Int. J. Comput. Assist. Radiol. Surg., September, 2024
2023
Dataset, November, 2023
Dataset, November, 2023
Dataset, June, 2023
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023
2022
Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison.
IEEE Trans. Artif. Intell., 2022
Segmentation of vertebrae and intervertebral discs in lumbar spine MR images with iterative instance segmentation.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
2021
Dataset, November, 2021
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.
Medical Image Anal., 2021
Medical Image Anal., 2021
2020
Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study.
CoRR, 2020
Random smooth gray value transformations for cross modality learning with gray value invariant networks.
CoRR, 2020
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images.
CoRR, 2020
2019
IEEE Trans. Medical Imaging, 2019
Iterative fully convolutional neural networks for automatic vertebra segmentation and identification.
Medical Image Anal., 2019
Automatic brain tissue segmentation in fetal MRI using convolutional neural networks.
CoRR, 2019
Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning.
Proceedings of the Medical Imaging 2019: Image Processing, 2019
2018
Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.
IEEE Trans. Medical Imaging, 2018
Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis.
Medical Image Anal., 2018
CoRR, 2018
Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images.
Proceedings of the Medical Imaging 2018: Image Processing, 2018
2017
2016
Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
2014
Feasibility of respiratory motion-compensated stereoscopic X-ray tracking for bronchoscopy.
Int. J. Comput. Assist. Radiol. Surg., 2014
2012
Ein Ansatz zur bewegungskompensierten stereoskopischen Navigation für die Bronchoskopie.
Proceedings of the 11. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie, 2012