Searched for: subject%3A%22Radiomics%22
(1 - 17 of 17)
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Chen, Linda (author)
Background: Histopathological examination in the diagnostic workflow of oropharyngeal squamous cell carcinoma (OPSCC) is essential. We aimed to develop a machine learning pipeline to predict human papillomavirus (HPV) status in OPSCC patients based on clinical variables and multiparametric magnetic resonance imaging (MRI). <br/>Methods: In a...
master thesis 2023
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van Gurp, Samuel (author)
Background: Histopathological growth patterns (HGP) are a biomarker for predicting survival and systemic treatment effectiveness in colorectal liver metastasis (CRLM). Currently, HGP assessment in CRLM requires the resection specimen. Predicting the HGP from preoperative medical imaging could allow more personalised care and better outcomes....
master thesis 2023
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Goedhart, Aisha (author)
Primary liver cancer is a commonly diagnosed cancer and accurate diagnosis is crucial for treatment planning. To differentiate between malignant and benign liver tumors, contrast-enhanced MRI is typically used as it provides information over multiple contrast phases. However, diagnosis based on MRI is challenging. In this study, automatic...
master thesis 2023
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Abler, Daniel (author), Schaer, Roger (author), Oreiller, Valentin (author), Verma, H. (author), Reichenbach, Julien (author), Aidonopoulos, Orfeas (author), Evéquoz, Florian (author), Jreige, Mario (author), Prior, John (author)
Background: Radiomics, the field of image-based computational medical biomarker research, has experienced rapid growth over the past decade due to its potential to revolutionize the development of personalized decision support models. However, despite its research momentum and important advances toward methodological standardization, the...
journal article 2023
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van der Voort, Sebastian R. (author), Incekara, Fatih (author), Wijnenga, Maarten M.J. (author), Kapsas, Georgios (author), Schouten, J.W. (author), French, P.J. (author), Niessen, W.J. (author), Smits, M. (author), Klein, Stefan (author)
BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can either non-invasively predict the genetic or histological features of glioma, or that can...
journal article 2023
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Heijdra, Amber (author)
Hypertrophic cardiomyopathy (HCM) is known as a frequent, genetic cardiovascular disease, often caused by mutations of sarcomere protein genes. HCM is primarily characterized by the presence of an increased left ventricular wall thickness, i.e. left ventricular hypertrophy (LVH). However, the disease appears to be asymptomatic in some patients,...
master thesis 2022
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Starmans, Martijn P.A. (author), Timbergen, Milea J.M. (author), Vos, Melissa (author), Renckens, Michel (author), Grünhagen, Dirk J. (author), van Leenders, Geert J.L.H. (author), Niessen, W.J. (author), Visser, Jacob J. (author), Klein, Stefan (author)
Treatment planning of gastrointestinal stromal tumors (GISTs) includes distinguishing GISTs from other intra-abdominal tumors and GISTs’ molecular analysis. The aim of this study was to evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors, and in GISTs, predict the c-KIT, PDGFRA, BRAF mutational status, and mitotic...
journal article 2022
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Castillo, J.M. (author), Arif, M. (author), Starmans, M.P.A. (author), Niessen, W.J. (author), Bangma, C.H. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)
The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning-and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods,...
journal article 2022
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Kalisvaart, Gijsbert M. (author), van Velden, Floris H.P. (author), Hernández-Girón, Irene (author), Meijer, Karin M. (author), Ghesquiere-Dierickx, Laura M.H. (author), Brink, Wyger M. (author), Webb, A. (author), de Geus-Oei, Lioe-Fee (author), Slump, Cornelis H. (author), Kuznetsov, D.V. (author), Schaart, D.R. (author), Grootjans, Willem (author)
Background: Accuracy and precision assessment in radiomic features is important for the determination of their potential to characterize cancer lesions. In this regard, simulation of different imaging conditions using specialized phantoms is increasingly being investigated. In this study, the design and evaluation of a modular multimodality...
journal article 2022
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Deen, Mitchell (author)
Recent years have shown a tremendous increase in the application of Artificial Intelligence to the field of radiology, often through the extraction and analysis of large numbers of quantitative features from medical images. These applications increase the demand for machine learning models to extract information from these images. To provide...
master thesis 2021
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Castillo, J.M. (author), Starmans, M.P.A. (author), Arif, M. (author), Niessen, W.J. (author), Klein, Stefan (author), Bangma, Chris H. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)
Radiomics applied in MRI has shown promising results in classifying prostate cancer lesions. However, many papers describe single-center studies without external validation. The issues of using radiomics models on unseen data have not yet been sufficiently addressed. The aim of this study is to evaluate the generalizability of radiomics...
journal article 2021
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Noortman, Wyanne A. (author), Vriens, Dennis (author), Mooij, C.D.Y. (author), Slump, Cornelis H. (author), Aarntzen, Erik H. (author), van Berkel, Anouk (author), Timmers, Henri J.L.M. (author), Bussink, Johan (author), Meijer, Tineke W.H. (author), de Geus-Oei, Lioe Fee (author), van Velden, Floris H.P. (author)
Background: Central necrosis can be detected on [<sup>18</sup>F]FDG PET/CT as a region with little to no tracer uptake. Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects...
journal article 2021
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Guo, Rui (author), Weingärtner, S.D. (author), Šiuryté, P. (author), T. Stoeck, Christian (author), Füetterer, Maximilian (author), E. Campbell-Washburn, Adrienne (author), Suinesiaputra, Avan (author), Jerosch-Herold, Michael (author), Nezafat, Reza (author)
Cardiovascular disease is the leading cause of death and a significant contributor of health care costs. Noninvasive imaging plays an essential role in the management of patients with cardiovascular disease. Cardiac magnetic resonance (MR) can noninvasively assess heart and vascular abnormalities, including biventricular structure/function,...
review 2021
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Castillo, Jose M.T. (author), Arif, Muhammad (author), Niessen, W.J. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)
Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep learning approaches has gained much interest, due to the potential application in assisting in clinical decision-making. Objective: To systematically review the literature (i) to determine which algorithms are most frequently used for sPCa classification...
journal article 2020
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Timbergen, Milea J.M. (author), Starmans, Martijn P.A. (author), Padmos, Guillaume A. (author), Grünhagen, Dirk J. (author), van Leenders, Geert J.L.H. (author), Hanff, D. F. (author), Niessen, W.J. (author), Klein, S. (author), Visser, J.J. (author)
Purpose: Diagnosing desmoid-type fibromatosis (DTF) requires an invasive tissue biopsy with β-catenin staining and CTNNB1 mutational analysis, and is challenging due to its rarity. The aim of this study was to evaluate radiomics for distinguishing DTF from soft tissue sarcomas (STS), and in DTF, for predicting the CTNNB1 mutation types....
journal article 2020
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Chatzoudis, Pavlos (author)
Prostate cancer is a disease with very high prevalence and mortality in the western world. An early accurate diagnosis can increase treatment efficiency. Current diagnosing techniques consist in systematic biopsy sampling. Radiomics can infer tumor's phenotypic differentiations from medical images, providing an accurate guide for biopsy sampling...
master thesis 2018
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Starmans, Martijn P.A. (author), Miclea, Razvan L. (author), van der Voort, S.R. (author), Niessen, W.J. (author), Thomeer, Maarten G. (author), Klein, S. (author)
Correct diagnosis of the liver tumor phenotype is crucial for treatment planning, especially the distinction between malignant and benign lesions. Clinical practice includes manual scoring of the tumors on Magnetic Resonance (MR) images by a radiologist. As this is challenging and subjective, it is often followed by a biopsy. In this study,...
conference paper 2018
Searched for: subject%3A%22Radiomics%22
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