Nikolas Lessmann

PhD candidate
e-mail: n.lessmann@umcutrecht.nl
Phone: +31 88 75 56682
Linkedin: https://nl.linkedin.com/in/nikolas-lessmann-231758105


Biography:

Nikolas studied Biomedical Engineering at the University of Lübeck, Germany. For his Bachelor’s thesis, he worked on X-ray based tracking to improve transbronchial biopsy of pulmonary nodules. He then spent one year at Philips Research in Hamburg, where he worked on automatic analysis of chest CT images for the detection of pulmonary embolism and on automatic segmentation of the pulmonary lobes. He is currently working on automatic calcium scoring and early detection of osteoporosis in lung cancer CT screening.


Papers in international journals

1.M. Zreik, N. Lessmann, R. van Hamersvelt, J.M. Wolterink, M. Voskuil, M.A. Viergever, T. Leiner, I. Išgum. Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis. Medical Image Analysis, 2018, vol. 44, pp. 72-85 Abstract | pdf )
2.N. Lessmann, B. van Ginneken, M. Zreik, P.A. de Jong, B.D. de Vos, M.A. Viergever, I. Išgum. Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions. IEEE Transactions on Medical Imaging, in press, 2017 Abstract | pdf )
3.E. Pompe, P.A. de Jong, D.A. Lynch, N. Lessmann, I. Isgum, B. van Ginneken, J.-W.J. Lammers, F.A.A. Mohamed Hoesein. Computed tomographic findings in subjects who died from respiratory disease in the National Lung Screening Trial. European Respiratory Journal, 2017, vol. 49, pp. 1601814 Abstract | pdf )

Papers in conference proceedings

1.N. Lessmann, B. van Ginneken, I. Isgum. Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images. In: SPIE Medical Imaging, in press, 2018 Abstract )
2.N. Lessmann, I. Isgum, A.A.A. Setio, B.D. de Vos, F. Ciompi, P.A. de Jong, M. Oudkerk, W.P.Th.M. Mali, M.A. Viergever, B. van Ginneken. Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT. In: SPIE Medical Imaging, 2016, vol. 9785, pp. 978511-1-978511-6 Abstract | pdf )

Abstracts

1.N.Lessmann, B. van Ginneken, P.A. de Jong, W.B. Veldhuis, M.A. Viergever, I. Isgum. Deep learning analysis for automatic calcium scoring in routine chest CT. Radiological Society of North America, 103rd Annual Meeting, 2017 Abstract )
2.B.D. de Vos, N. Lessmann, P.A. de Jong, M.A. Viergever, I. Isgum. Direct coronary artery calcium scoring in low-dose chest CT using deep learning analysis. Radiological Society of North America, 103rd Annual Meeting, 2017 Abstract )
3.M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M.A Viergever, T. Leiner, I. Isgum . Deep learning analysis of the left ventricular myocardium in cardiac CT images enables detection of functionally significant coronary artery stenosis regardless of coronary anatomy. Radiological Society of North America, 103rd Annual Meeting , 2017 Abstract )
4.F. Mohamed Hoesein, E. Pompe, D.A. Lynch, N. Lessmann, J.W.J. Lammers, I. Isgum, P.A. de Jong. Computed tomographic findings are associated with respiratory mortality in the National Lung Screening Trial. Radiological Society of North America, 102nd Annual Meeting, 2016 Abstract )
5.N. Lessmann, I. Isgum, S. Lam, J. Mayo, P.A. de Jong, M.A. Viergever, B. van Ginneken. Automatic coronary calcium scoring and cardiovascular risk estimation in the Pan-Canadian lung cancer screening trial. Radiological Society of North America, 101th Annual Meeting, 2015 Abstract )