University of Groningen
Deep learning for lung cancer on computed tomography
Zheng, Sunyi
DOI:
10.33612/diss.171374829
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
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Publication date: 2021
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Zheng, S. (2021). Deep learning for lung cancer on computed tomography: early detection and prognostic prediction. University of Groningen. https://doi.org/10.33612/diss.171374829
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PUBLICATIONS
▶▶Publications in peer reviewed journals
S. Zheng, X. Cui, M. Vonder, R.N.J. Veldhuis, Z. Ye, R. Vliegenthart, M. Oudkerk, P.M.A. van Ooijen, “Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage”. Computer Methods and Programs in Biomedicine, 196: 105620, 2020.
X. Cui, M.A. Heuvelmans, S. Fan, D. Han, S. Zheng, Y. Du, Y. Zhao, G. Sidorenkov, H.J.M. Groen, M.D. Dorrius, M. Oudkerk, G.H. de Bock, R. Vliegenthart, Z. Ye, “A Subsolid Nodules Imaging Reporting System (SSN-IRS) for classifying three subtypes of pulmonary adenocarcinoma”. Clinical Lung Cancer, 21.4: 314-325, 2020.
S. Zheng, L.J. Cornelissen, X. Cui, X. Jing, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Deep convolutional neural networks for multi‐planar lung nodule detection: improvement in small nodule identification”. Medical Physics, 48(2): 733-744, 2020. X. Cui, M.A. Heuvelmans, D. Han, Y. Zhao, S. Fan, S. Zheng, G. Sidorenkov, H.J.M. Groen, M.D. Dorrius, M. Oudkerk, G.H. de Bock, R. Vliegenthart, Z. Ye, “Comparison of Veterans Affairs, Mayo, Brock classification models and radiologist diagnosis for classifying the malignancy of pulmonary nodules in Chinese clinical population”. Translational Lung Cancer Research, 8(5): 605, 2019.
S. Zheng, J. Guo, X. Cui, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Automatic pulmonary nodule detection in CT scans using convolutional neural networks based on maximum intensity projection”. IEEE transactions on medical imaging, 39.3: 797-805, 2019.
▶▶Papers submitted to international journals
M. Vonder, S. Zheng, M.D. Dorrius, C.M. van der Aalst, H.J. de Koning, J. Yi, D. Yu, J.W. Gratama, D.J. Kuijpers, M. Oudkerk, “Deep learning for automatic calcium scoring in population based cardiovascular screening”. Submitted, 2021.
S. Zheng, J. Guo, J.A. Langendijk, S. Both, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, R. Wijsman, N.M. Sijtsema, “Prognostic outcome prediction for early stage non-small cell lung cancer using deep learning”. Submitted, 2021.
X. Cui, M.A. Heuvelmans, S. Fan, D. Han, S. Zheng, Y. Du, Y. Zhao, G. Sidorenkov, H.J.M. Groen, M.D. Dorrius, M. Oudkerk, G.H. de Bock, R. Vliegenthart, Z. Ye, “A Contrast-Enhanced-CT-Based Classification Tree Model for Classifying Solid Lung Tumors in a Clinical Chinese Population as Malignant”. Submitted, 2021.
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Dorrius, S.P. Morozov, V.A. Gombolevsky, M. Oudkerk, “Volumetry versus linear diameter lung nodule measurement; an ultra-low-dose CT Lung Cancer Screening Study”. Submitted, 2021.
X. Jing, M. Wielema, L.J. Cornelissen, M. van Gent, W.M. Iwema, S. Zheng, P.E. Sijens, M. Oudkerk, M.D. Dorrius, P.M.A van Ooijen, “Artificial Intelligence-Based Single Breast Classification in Ultrafast DCE-MRI to Accelerate Breast Cancer Screening”. Submitted, 2021.
X. Cui *, S. Zheng *, M.A. Heuvelmans, Y. Du, G. Sidorenkov, S. Fan, Y. Li, Y. Xie, Z. Zhu, Y. Zhao, R.N.J. Veldhuis, M. Oudkerk, G.H. de Bock, P.M.A. van Ooijen, R. Vliegenthart, Z. Ye, “Performance of a deep learning-based lung nodule detection system as an assistant reader in a Chinese lung cancer screening program”. Submitted, 2021
▶▶Book chapter
S. Zheng, P.M.A. van Ooijen, M. Oudkerk, "The role of AI in Lung Cancer Screening and Nodule Detection". Artificial Intelligence in Cardiothoracic Imaging. Chapter 53, Springer, in press.
▶▶Conference abstracts
S. Zheng, J. Guo, J. A. Langendijk, S. Both, L.J. Cornelissen, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, R. Wijsman, N.M. Sijtsema, “Prognostic outcome prediction for early stage non-small cell lung cancer using deep learning”. IEEE 8th Dutch Bio-Medical Engineering Conference, 2021, Webinar.
S. Zheng, L.J. Cornelissen, X. Cui, X. Jing, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Multi-planar deep convolutional networks for nodule detection in CT scans”. IEEE 8th Dutch Bio-Medical Engineering Conference, 2021, Webinar.
X. Cui, S. Zheng, M. Heuvelmans, Y. Du, G. Sidorenkov, M. Dorrius, R.N.J Veldhuis, M. Oudkerk, G. De Bock, P.M.A Van Ooijen, R. Vliegenthart, Z. Ye, “Evaluating the Feasibility of a Deep Learning-Based Computer-Aided Detection System for Lung Nodule Detection in a Lung Cancer Screening Program”. IASLC World Conference on Lung Cancer, 2020, Webinar.
S. Zheng, X. Cui, M. Vonder, R.N.J Veldhuis, M. Dorrius, Z. Ye, R. Vliegenthart, M. Oudkerk, P.M.A van Ooijen, “Automatic Lung Nodule Detection by a Deep Learning-Based CAD System: The Value of Slab Thickness in the Maximum Intensity Projection Technique”. IASLC World Conference on Lung Cancer, 2020, Webinar.
X. Cui, S. Zheng, M. Heuvelmans, Y. Du, G. Sidorenkov, M. Dorrius, R.N.J Veldhuis, M. Oudkerk, G. De Bock, P.M.A van Ooijen, R. Vliegenthart, Z. Ye, “Validation of a deep learning-based computer-aided system for lung nodule detection in a Chinese lung cancer screening program”. European Respiratory Society International Congress, 2020, Webinar.
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S. Zheng, X. Cui, M. Vonder, R.N.J Veldhuis, M. Dorrius, Z. Ye, R. Vliegenthart, M. Oudkerk, P.M.A van Ooijen, “Effect of slab thickness on pulmonary nodule detection using maximum intensity projection in a deep learning-based computer-aided detection system”. European Respiratory Society International Congress, 2020, Webinar.
X. Cui, M.A. Heuvelmans, S. Zheng, H.J.M. Groen, M.D. Dorrius, M. Oudkerk, G.H. de Bock, R. Vliegenthart, Z. Ye, “Radiological classification of sub-solid lung nodules to differentiate the pulmonary adenocarcinoma”. European Congress of Radiology, 2020, Webinar.
X. Jing, M. Wielema, L.J. Cornelissen, S. Zheng, J. Guo, P.E. Sijens, M. Oudkerk, M.D. Dorrius, P.M.A van Ooijen, “Deep Learning-based Breast MRI Classification for Safely Ruling Out Unsuspicious Screening Exams”. European Society of Medical Imaging Informatics, 2019, Valencia, Spain.
S. Zheng, X. Cui, Z. Ye, G.H. de Bock, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Validation of a deep learning-based computer-aided system for detection of pulmonary nodules in low-dose CT scans”. European Society of Medical Imaging Informatics, 2019, Valencia, Spain.
S. Zheng, J. Guo, M. Rook, X. Cui, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Multi-MIP Views Convolutional Neural Networks for Lung Nodule Detection in CT Scans”. Medical Imaging Symposium, 2019, Groningen, the Netherlands
S. Zheng, J. Guo, M. Rook, X. Cui, R.N.J. Veldhuis, M. Oudkerk, P.M.A. van Ooijen, “Automatic Pulmonary Nodule Detection in Low-dose CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection”. European Congress of Radiology, 2019, Vienna, Austria.
Yeshaswini Nagaraj, Sunyi Zheng, Mieneke Rook, Qiong Li, Gert Jan Pelgrim, Matthijs Oudkerk, Peter van Ooijen. “Analysis of multi-parametric radiomics from low-dose CT scans for better discrimination between non-emphysematous and emphysematous lung tissue”. ESTI/ESCR Annual Meeting, 2018, Geneve, Switzerland
