N
Nikolas Lessmann
Researcher at Radboud University Nijmegen
Publications - 41
Citations - 1528
Nikolas Lessmann is an academic researcher from Radboud University Nijmegen. The author has contributed to research in topics: National Lung Screening Trial & Population. The author has an hindex of 14, co-authored 41 publications receiving 789 citations. Previous affiliations of Nikolas Lessmann include Utrecht University & Analysis Group.
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Journal ArticleDOI
Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions
Nikolas Lessmann,Bram van Ginneken,Majd Zreik,Pim A. de Jong,Bob D. de Vos,Max A. Viergever,Ivana Išgum +6 more
TL;DR: The presented method enables reliable automatic cardiovascular risk assessment in all low-dose chest CT scans acquired for lung cancer screening and is evaluated on a set of 1744 CT scans from the National Lung Screening Trial.
Journal ArticleDOI
Iterative fully convolutional neural networks for automatic vertebra segmentation and identification
TL;DR: An iterative instance segmentation approach that uses a fully convolutional neural network to segment and label vertebrae one after the other, independently of the number of visible vertebraes is proposed and compares favorably with state‐of‐the‐art methods.
Journal ArticleDOI
Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis
Majd Zreik,Nikolas Lessmann,Robbert W. van Hamersvelt,Jelmer M. Wolterink,Michiel Voskuil,Max A. Viergever,Tim Leiner,Ivana Išgum +7 more
TL;DR: The results demonstrate that automatic analysis of the LV myocardium in a single CCTA scan acquired at rest, without assessment of the anatomy of the coronary arteries, can be used to identify patients with functionally significant coronary artery stenosis, and may potentially reduce the number of patients undergoing unnecessary invasive FFR measurements.
Journal ArticleDOI
Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.
Sanne G M van Velzen,Nikolas Lessmann,B. K. Velthuis,Ingrid E.M. Bank,Desirée H.J.G. van den Bongard,Tim Leiner,Pim de Jong,Wouter B. Veldhuis,Adolfo Correa,James G. Terry,J. Jeffrey Carr,Max A. Viergever,Helena M. Verkooijen,Ivana Išgum +13 more
TL;DR: A deep learning calcium scoring algorithm for quantification of coronary and thoracic calcium was robust, despite substantial differences in CT protocol and variations in subject population.
Journal ArticleDOI
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina,Malek El Husseini,Amirhossein Bayat,Maximilian T. Löffler,Hans Liebl,Hongwei Li,Giles Tetteh,Jan Kukačka,Christian Payer,Darko Štern,Martin Urschler,Maodong Chen,Dalong Cheng,Nikolas Lessmann,Yujin Hu,Tianfu Wang,Dong Yang,Daguang Xu,Felix Ambellan,Tamaz Amiranashvili,Moritz Ehlke,Hans Lamecker,Sebastian Lehnert,Marilia Lirio,Nicolás Pérez de Olaguer,Heiko Ramm,Manish Sahu,Alexander Tack,Stefan Zachow,Tao Jiang,Xinjun Ma,Christoph Angerman,Xin Wang,Kevin W. Brown,Alexandre Kirszenberg,Elodie Puybareau,Di Chen,Yiwei Bai,Brandon H. Rapazzo,Timyoas Yeah,Amber Zhang,Shangliang Xu,Feng Hou,Zhiqiang He,Chan Zeng,Zheng Xiangshang,Xu Liming,Tucker Netherton,Raymond P. Mumme,Laurence E. Court,Zixun Huang,Chenhang He,Li-Wen Wang,Sai Ho Ling,Lê Duy Huỳnh,Nicolas Boutry,Roman Jakubicek,Jiri Chmelik,Supriti Mulay,Mohanasankar Sivaprakasam,Johannes C. Paetzold,Suprosanna Shit,Ivan Ezhov,Benedikt Wiestler,Ben Glocker,Alexander Valentinitsch,Markus Rempfler,Björn H. Menze,Jan S. Kirschke +68 more
TL;DR: The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations.