Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 19 of 19 for “"Radiomic features"”.
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Stability and Robustness of Radiomic Features Due to Volumetric Uncertainty in Pancreatic Cancer
Soaring interest in radiomics research seeks to identify quantitative imaging features for enhanced clinical decision support. The radiomics analysis workflow involves image acquisition followed by volume segmentation. Features such as tumor shape or texture (such as how 'smooth' or 'irregular' the …
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Krūties vėžio magnetinio rezonanso vaizdo tekstūros analizė /
… the efficacy of magnetic resonance imaging radiomics in the detection of breast cancer linked to BRCA1 and BRCA2 gene mutations and to identify precise radiomic features that could develop new non-invasive breast cancer diagnostic approaches, oriented at genetics. Methods: A prospective …
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Survival analysis for lung cancer patients
… and provides in-depth analysis of different features influencing lung cancer prognosis. We added nodule annotations to the NLST dataset and extracted radiomic features from each nodule. Using the newly acquired radiomic features, coupled with the existing clinical data from the original NLST …
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Towards Robust Radiomic Markers from Positron Emission Tomography in Cancer
… The latter can be accessed computationally using radiomics, from which we can build new markers of disease to improve the clinical management of patients. However, the generation and handling of PET images is a multifactorial process, and so careful consideration of these factors is required to …
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Radiomics and Machine Learning in the Prediction of Cardiovascular Disease
… that can be obtained from a carotid CTA scan. Radiomics, sometimes called ‘texture analysis’, is the extraction of quantitative data from medical images that may not be apparent to the naked eye and has already demonstrated clinical utility in oncology for applications ranging from lesion …
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Combination of CT-based Radiomics Features and Clinical Data for Predicting Tumor Genetic Profile in patients with Intrahepatic Cholangiocarcinoma
… Objective: This study aims to determine whether radiomic features extracted from contrast-enhanced CT scans can predict iCCA genetic alterations non-invasively. Methods: Consecutive patients diagnosed with mass-forming iCCA between January 2016 and June 2022 were included. Criteria for inclusion …
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Classification of atherosclerotic plaque vulnerability by mechano-radiomics
… the hypothesis that combined biomechanical and radiomic features (mechano-radiomics) from magnetic resonance (MR) images can help evaluate carotid plaque vulnerability better than conventional MR methods. Hemodynamic forces have long been associated with the destabilization of developed plaques …
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Unravelling the Spatial and Temporal Heterogeneity of High-Grade Serous Ovarian Cancer Using Imaging-Based Biomarkers
… diagnosis, prognosis and treatment response. Radiomics, an emerging computational approach, offers a promising non-invasive method to assess tumour heterogeneity using radiological images. The biological validation of radiomic features (e.g. through genomics, proteomics or transcriptomics) …
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Integration of Biomedical Imaging and Translational Approaches For Management of Head and Neck Cancer
… component of this work, we integrated radiomic features derived from pre-RT CT images with whole-genome measurements using TCGA and TCIA data. Our results demonstrated a statistically significant associations between radiomic features characterizing different tumor phenotypes and …
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Bronchial gene expression associated with airway pre-malignancy and lung cancer subtypes
… the bronchial airway molecular biomarker with radiomic features (i.e., quantitative features derived from radiographic images) could yield a better diagnosis for lung cancer screening. Using clinical variables, molecular signatures, and radiomic imaging features, I built and tested an …
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Domain and User-Centered Machine Learning for Medical Image Analysis
… improves the stability of handcrafted radiomic features extracted from brain MRIs. Second, the selected network design must be appropriate for a specific task. Here, we illustrate the advantages of shifting from a strictly discrete (ordinal) model of disease severity distribution to a …
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RADIOMICS FOR OUTCOME PREDICTION IN EARLY-STAGE NON-SMALL CELL LUNG CANCER PATIENTS TREATED WITH STEREOTACTIC BODY RADIOTHERAPY (SBRT): METHODOLOGICAL CHALLENGES AND CLINICAL APPLICATIONS
… practice. This field of study, referred to as radiomics, is the subject of several investigations, on multiple disease sites. Of these, Non-Small Cell Lung Cancer (NSCLC) is a good model of study, not only for its relevance- being one of the so-called “big killers” in Oncology- but also for the …
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Characterising Heterogeneity of Glioblastoma using Multi-parametric Magnetic Resonance Imaging
… 3) the value of advanced physiological MRI and radiomics approach in predicting epigenetic phenotypes (V). The following observations were made: I. Using a joint histogram analysis method, habitats with different diffusivity patterns were identified. A non-enhancing sub-region with decreased …
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A Systems Approach to Modelling Tumour and Tissue Response in Radiotherapy for Head-and-Neck Cancer
… cancer datasets. Tumour-level analyses applied a radiomic pipeline to clinical target volumes (CTVs) extracted from planning CT scans, for the development of predictive models for recurrence risk. These models achieved up to 82% accuracy for internal datasets, demonstrating the potential of …
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Prediction of Coronary Atherosclerosis Development: A Study Based on the Combination of Mechanomics and Radiomics
… data from coronary CTA, including direct radiomic and morphological features, as well as indirect features from CFD simulations, to analyse correlations and develop predictive models for atherosclerosis development proximal to myocardial bridging (MB). To manage a relatively large dataset …
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Artificial Intelligence (AI)-assisted Cardiotoxicity Management in Lung Cancer Radiotherapy
… of clinical factors, dosimetric parameters, and radiomic features derived from both whole-heart and substructure-based metrics using two independent datasets. The findings demonstrated that cardiac substructure dosimetric parameters exhibited superior predictive performance, with left anterior …
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Computational imaging and multiomic biomarkers for precision medicine: characterizing heterogeneity in lung cancer.
… characterize intratumor heterogeneity. A novel radiomic biomarker, that integrates with PDL1 expression, ECOG status, BMI, and smoking status, to enhance the ability to predict progression-free survival in a preliminary cohort of patients with stage 4 NSCLC, treated with first-line anti-PD1/PDL1 …