نتایج جستجو برای: radiomics

تعداد نتایج: 1808  

2016
Hugo J. W. L. Aerts Patrick Grossmann Yongqiang Tan Geoffrey R. Oxnard Naiyer Rizvi Lawrence H. Schwartz Binsheng Zhao

Medical imaging plays a fundamental role in oncology and drug development, by providing a non-invasive method to visualize tumor phenotype. Radiomics can quantify this phenotype comprehensively by applying image-characterization algorithms, and may provide important information beyond tumor size or burden. In this study, we investigated if radiomics can identify a gefitinib response-phenotype, ...

2017
Patrick Grossmann Olya Stringfield Nehme El-Hachem Marilyn M Bui Emmanuel Rios Velazquez Chintan Parmar Ralph Th Leijenaar Benjamin Haibe-Kains Philippe Lambin Robert J Gillies Hugo Jwl Aerts

Medical imaging can visualize characteristics of human cancer noninvasively. Radiomics is an emerging field that translates these medical images into quantitative data to enable phenotypic profiling of tumors. While radiomics has been associated with several clinical endpoints, the complex relationships of radiomics, clinical factors, and tumor biology are largely unknown. To this end, we analy...

2014
Hugo J. W. L. Aerts Emmanuel Rios Velazquez Ralph T. H. Leijenaar Chintan Parmar Patrick Grossmann Sara Cavalho Johan Bussink René Monshouwer Benjamin Haibe-Kains Derek Rietveld Frank Hoebers Michelle M. Rietbergen C. René Leemans Andre Dekker John Quackenbush Robert J. Gillies Philippe Lambin

Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical imaging. Radiomics refers to the comprehensive quantification of tumour phenotypes by applying a large number of quantitative image features. Here we present a radiomic analysis of 440 features quantifying tumour image intensity, shape and texture, which are extracted from computed tomography dat...

Journal: :AJNR. American journal of neuroradiology 2018
M Zhou J Scott B Chaudhury L Hall D Goldgof K W Yeom M Iv Y Ou J Kalpathy-Cramer S Napel R Gillies O Gevaert R Gatenby

Radiomics describes a broad set of computational methods that extract quantitative features from radiographic images. The resulting features can be used to inform imaging diagnosis, prognosis, and therapy response in oncology. However, major challenges remain for methodologic developments to optimize feature extraction and provide rapid information flow in clinical settings. Equally important, ...

2016
Jacob Antunes Satish Viswanath Mirabela Rusu Laia Valls Christopher Hoimes Norbert Avril Anant Madabhushi

Studying early response to cancer treatment is significant for patient treatment stratification and follow-up. Although recent advances in positron emission tomography (PET) and magnetic resonance imaging (MRI) allow for evaluation of tumor response, a quantitative objective assessment of treatment-related effects offers localization and quantification of structural and functional changes in th...

2016
Weimiao Wu Chintan Parmar Patrick Grossmann John Quackenbush Philippe Lambin Johan Bussink Raymond Mak Hugo J. W. L. Aerts

BACKGROUND Radiomics can quantify tumor phenotypic characteristics non-invasively by applying feature algorithms to medical imaging data. In this study of lung cancer patients, we investigated the association between radiomic features and the tumor histologic subtypes (adenocarcinoma and squamous cell carcinoma). Furthermore, in order to predict histologic subtypes, we employed machine-learning...

Journal: : 2022

Introduction MRI semiotics in the differential diagnosis of primary extra-axial intracranial tumors (PEIT) Localization tumor and its relationship with anatomical structures Heterogeneity (heterogeneity) Tumor margins peritumoral edema Apparent diffusion coefficient (ADC) Dural tail sign Information technology for analysis radiomics Radiomics PEIT Conclusion

Journal: :NeuroImage: Clinical 2017
Arman Rahmim Peng Huang Nikolay Shenkov Sima Fotouhi Esmaeil Davoodi-Bojd Lijun Lu Zoltan Mari Hamid Soltanian-Zadeh Vesna Sossi

Journal: :Circulation-cardiovascular Imaging 2021

Radiomics uses advanced image analysis to extract massive amounts of quantitative information from digital images, which is not otherwise distinguishable the human eye. The mined data can be used explore and establish new undiscovered correlations between these imaging features clinical end points. Cardiac computed tomography (CT) a first-line modality for evaluating coronary artery disease has...

Journal: :Physics in medicine and biology 2016
Stephen S F Yip Hugo J W L Aerts

Radiomics is an emerging field in quantitative imaging that uses advanced imaging features to objectively and quantitatively describe tumour phenotypes. Radiomic features have recently drawn considerable interest due to its potential predictive power for treatment outcomes and cancer genetics, which may have important applications in personalized medicine. In this technical review, we describe ...

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