Nikolas Leßmann

Orcid: 0000-0001-7935-9611

According to our database1, Nikolas Leßmann authored at least 30 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

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

Semi-Supervised Segmentation via Embedding Matching.
CoRR, 2024

2023
SPIDER - Lumbar spine segmentation in MR images: a dataset and a public benchmark.
Dataset, November, 2023

SPIDER - Lumbar spine segmentation in MR images: a dataset and a public benchmark.
Dataset, November, 2023


Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.
IEEE Trans. Medical Imaging, March, 2023

Transfer learning from a sparsely annotated dataset of 3D medical images.
CoRR, 2023

Kidney abnormality segmentation in thorax-abdomen CT scans.
CoRR, 2023

Lumbar spine segmentation in MR images: a dataset and a public benchmark.
CoRR, 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
SPIDER - Lumbar spine segmentation in MR images: a dataset and a public benchmark.
Dataset, November, 2021

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.
Medical Image Anal., 2021

CNN-based lung CT registration with multiple anatomical constraints.
Medical Image Anal., 2021

2020
Constraining Volume Change in Learned Image Registration for Lung CTs.
CoRR, 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
Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT.
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

Iterative fully convolutional neural networks for automatic vertebra segmentation.
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
Direct and Real-Time Cardiovascular Risk Prediction.
CoRR, 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


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