Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Ivan Zhovannik"'
Autor:
Ivan Zhovannik, Suraj Pai, Talia A. da Silva Santos, Lars L.G. van Driel, Andre Dekker, Rianne Fijten, Alberto Traverso, Johan Bussink, René Monshouwer
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 20, Iss , Pp 30-33 (2021)
Radiomics is referred to as quantitative imaging of biomarkers used for clinical outcome prognosis or tumor characterization. In order to bridge radiomics and its clinical application, we aimed to build an integrated solution of radiomics extraction
Externí odkaz:
https://doaj.org/article/19c536ac9003418f91255ea2d0765678
Autor:
Elisabeth Pfaehler, Ivan Zhovannik, Lise Wei, Ronald Boellaard, Andre Dekker, René Monshouwer, Issam El Naqa, Jan Bussink, Robert Gillies, Leonard Wee, Alberto Traverso
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 20, Iss , Pp 69-75 (2021)
Background and Purpose: Although quantitative image biomarkers (radiomics) show promising value for cancer diagnosis, prognosis, and treatment assessment, these biomarkers still lack reproducibility. In this systematic review, we aimed to assess the
Externí odkaz:
https://doaj.org/article/7555f1f9a7b74a5bb49c2ff4bb27b386
Frequency-Domain-Based Structure Losses for CycleGAN-Based Cone-Beam Computed Tomography Translation
Autor:
Suraj Pai, Ibrahim Hadzic, Chinmay Rao, Ivan Zhovannik, Andre Dekker, Alberto Traverso, Stylianos Asteriadis, Enrique Hortal
Publikováno v:
Sensors, Vol 23, Iss 3, p 1089 (2023)
Research exploring CycleGAN-based synthetic image generation has recently accelerated in the medical community due to its ability to leverage unpaired images effectively. However, a commonly established drawback of the CycleGAN, the introduction of a
Externí odkaz:
https://doaj.org/article/5b258dac8f7543cbad0b762c442c753a
Autor:
Ivan Zhovannik, Johan Bussink, Alberto Traverso, Zhenwei Shi, Petros Kalendralis, Leonard Wee, Andre Dekker, Rianne Fijten, René Monshouwer
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 19, Iss , Pp 33-38 (2019)
Purpose: Radiomics are quantitative features extracted from medical images. Many radiomic features depend not only on tumor properties, but also on non-tumor related factors such as scanner signal-to-noise ratio (SNR), reconstruction kernel and other
Externí odkaz:
https://doaj.org/article/e464fd7ca9d0442081c5d0c67d4ed65d
Autor:
Ivan Zhovannik, Dennis Bontempi, Alessio Romita, Elisabeth Pfaehler, Sergey Primakov, Andre Dekker, Johan Bussink, Alberto Traverso, René Monshouwer
Publikováno v:
Cancers, Vol 14, Iss 5, p 1288 (2022)
Problem. Image biomarker analysis, also known as radiomics, is a tool for tissue characterization and treatment prognosis that relies on routinely acquired clinical images and delineations. Due to the uncertainty in image acquisition, processing, and
Externí odkaz:
https://doaj.org/article/84c902b5d5e64c9ea8ebadd0b0831e77
Autor:
Rianne Fijten, Andre Dekker, Lars L.G. van Driel, René Monshouwer, Alberto Traverso, Talia A. da Silva Santos, Ivan Zhovannik, Johan Bussink, Suraj Pai
Publikováno v:
Physics and Imaging in Radiation Oncology, 20, 30-33
Physics & Imaging in Radiation Oncology, 20, 30-33. Elsevier Ireland Ltd
Physics and Imaging in Radiation Oncology, 20, pp. 30-33
Physics and Imaging in Radiation Oncology, Vol 20, Iss, Pp 30-33 (2021)
Physics and Imaging in Radiation Oncology
Physics & Imaging in Radiation Oncology, 20, 30-33. Elsevier Ireland Ltd
Physics and Imaging in Radiation Oncology, 20, pp. 30-33
Physics and Imaging in Radiation Oncology, Vol 20, Iss, Pp 30-33 (2021)
Physics and Imaging in Radiation Oncology
Graphical abstract
Radiomics is referred to as quantitative imaging of biomarkers used for clinical outcome prognosis or tumor characterization. In order to bridge radiomics and its clinical application, we aimed to build an integrated solution
Radiomics is referred to as quantitative imaging of biomarkers used for clinical outcome prognosis or tumor characterization. In order to bridge radiomics and its clinical application, we aimed to build an integrated solution
Autor:
Jan Bussink, Elisabeth Pfaehler, Ivan Zhovannik, Ronald Boellaard, Alberto Traverso, Lise Wei, Andre Dekker, René Monshouwer, Robert J. Gillies, Leonard Wee, Issam El Naqa
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 20, Iss, Pp 69-75 (2021)
Physics and Imaging in Radiation Oncology, 20, pp. 69-75
Physics and Imaging in Radiation Oncology, 20, 69-75
Pfaehler, E, Zhovannik, I, Wei, L, Boellaard, R, Dekker, A, Monshouwer, R, el Naqa, I, Bussink, J, Gillies, R, Wee, L & Traverso, A 2021, ' A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features ', Physics and Imaging in Radiation Oncology, vol. 20, pp. 69-75 . https://doi.org/10.1016/j.phro.2021.10.007
Physics and Imaging in Radiation Oncology
Physics and Imaging in Radiation Oncology, 20, pp. 69-75
Physics and Imaging in Radiation Oncology, 20, 69-75
Pfaehler, E, Zhovannik, I, Wei, L, Boellaard, R, Dekker, A, Monshouwer, R, el Naqa, I, Bussink, J, Gillies, R, Wee, L & Traverso, A 2021, ' A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features ', Physics and Imaging in Radiation Oncology, vol. 20, pp. 69-75 . https://doi.org/10.1016/j.phro.2021.10.007
Physics and Imaging in Radiation Oncology
Highlights • Main factors impacting feature stability: Image acquisition, reconstruction, tumor segmentation, and interpolation. • Textural features are less robust than morphological or statistical features. • A checklist is provided including
Autor:
Matthijs Sloep, Petros Kalendralis, Ivan Zhovannik, Zhenwei Shi, Martijn P. A. Starmans, Hugo J.W.L. Aerts, Stefan Klein, Detlef Grittner, Ananya Choudhury, Andre Dekker, Rianne Fijten, Johan van Soest, Alberto Traverso, Leonard Wee, Peter Feltens, René Monshouwer
Publikováno v:
Medical Physics, 47, 5931-5940
Medical Physics, 47(11), 5931-5940. Wiley
Medical Physics, 47, 11, pp. 5931-5940
Medical Physics
Medical Physics, 47(11), 5931-5940. John Wiley & Sons Ltd.
Medical Physics, 47(11), 5931-5940. Wiley
Medical Physics, 47, 11, pp. 5931-5940
Medical Physics
Medical Physics, 47(11), 5931-5940. John Wiley & Sons Ltd.
Contains fulltext : 229874.pdf (Publisher’s version ) (Open Access) PURPOSE: One of the most frequently cited radiomics investigations showed that features automatically extracted from routine clinical images could be used in prognostic modeling. T
Autor:
Leonard Wee, Rianne Fijten, Alberto Traverso, Andre Dekker, Petros Kalendralis, Ivan Zhovannik, Zhenwei Shi, René Monshouwer, Johan Bussink
Publikováno v:
Clinical and Translational Radiation Oncology, Vol 19, Iss, Pp 33-38 (2019)
Clinical and Translational Radiation Oncology, 19, pp. 33-38
Clinical and Translational Radiation Oncology, 19, 33-38. Elsevier Ireland Ltd
Clinical and Translational Radiation Oncology, 19, 33-38
Clinical and Translational Radiation Oncology
Clinical and Translational Radiation Oncology, 19, pp. 33-38
Clinical and Translational Radiation Oncology, 19, 33-38. Elsevier Ireland Ltd
Clinical and Translational Radiation Oncology, 19, 33-38
Clinical and Translational Radiation Oncology
Highlights • Typically encountered CT exposure variations result in radiomics values distortion. • Proposed correction method suppresses the non-tumor related variation in radiomics. • The clinical relevance was shown using a 221 lung cancer pa
Distributed radiomics as a signature validation study using the Personal Health Train infrastructure
Autor:
Johan Bussink, Andre Dekker, Frank J. W. M. Dankers, Hugo J.W.L. Aerts, Petros Kalendralis, Rianne Fijten, Alberto Traverso, Leonard Wee, Timo M. Deist, René Monshouwer, Ivan Zhovannik, Zhenwei Shi
Publikováno v:
Scientific Data, Vol 6, Iss 1, Pp 1-8 (2019)
Scientific Data, 6
Scientific Data
Scientific data, 6:218. Nature Publishing Group
Scientific Data, 6
Scientific Data
Scientific data, 6:218. Nature Publishing Group
Prediction modelling with radiomics is a rapidly developing research topic that requires access to vast amounts of imaging data. Methods that work on decentralized data are urgently needed, because of concerns about patient privacy. Previously publis