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 20 of 40 for “"Radiomics"”.
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Classification of atherosclerotic plaque vulnerability by mechano-radiomics
… 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 near regions of complex …
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Deep Learning and Radiomics Based Outcome Prediction for Cancer Patients
… learning methods, such as deep learning (DL) and radiomics, has been gaining attention in the field of cancer research for predicting treatment outcomes. In this dissertation, we present a comprehensive study on developing deep learning and radiomics-based models for outcome prediction in various …
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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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Non-Invasive cancer detection: computational applications in liquid biopsy and radiomics
… part of the thesis investigates the potential of radiomics in predicting treatment response in lung cancer patients. This exploration aims to complement liquid biopsy approaches by incorporating quantitative features extracted from medical images.
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MRI Radiomics Modeling and Survival Prediction of Pancreatic Ductal Adenocarcinoma Patients
… disease.Quantitative imaging analysis, namely radiomics, has been gaining popularity in medicine over recent years in identifying cancer variants that are particularly difficult to diagnose when symptoms are absent. In addition, radiomics is becoming a valuable tool for patient prognosis and to …
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Radiomics of Nsclc: Quantitative Ct Image Feature Characterization and Tumor Shrinkage Prediction
<p>Radiomics is the high-throughput extraction and analysis of quantitative image features. For non-small cell lung cancer (NSCLC) patients, radiomics can be applied to standard of care computed tomography (CT) images to improve tumor diagnosis, staging, and response assessment.</p> <p>The first …
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HYBRID DEEP LEARNING AND RADIOMICS MODELS FOR ASSESSMENT OF CLINICALLY RELEVANT PROSTATE CANCER
… especially in the assessment of cancer, is radiomics; the practice of characterizing images by extracting a substantial amount of quantitative mathematical descriptors. This success has largely been enabled by artificial intelligence (AI) and machine learning developments that are capable of …
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Exploring Radiomics and Unveiling Novel Qualitative Imaging Biomarkers for Glioma Diagnosis in Dogs
Radiomics integrates machine learning (ML) and radiology to extract and analyze quantitative features from medical imaging modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), ultrasound (US) and digital radiographs (DX). By extracting …
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Prediction of Coronary Atherosclerosis Development: A Study Based on the Combination of Mechanomics and Radiomics
Atherosclerosis is the precursor to cardiovascular diseases (CVDs), the leading cause of death and disability globally. Coronary artery disease (CAD) from atherosclerosis significantly contributes to CVDs. Despite their primary role in delivering oxygenated blood to the myocardium, the anatomical …
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CLASSIFICATION OF PATIENTS WITH PAROTID CANCER USING DYNAMIC CONTRAST AND DIFFUSION EXAMINATIONS WITH RADIOMICS AND MACHINE LEARNING TECHNIQUES
… this study is to evaluate the role of MRI-based radiomics analysis and machine learning using both DWI with multiples B values and dynamic contrast-enhanced T1-weighted sequences to differentiate pleomorphic adenoma (A), Warthin’s tumor (W) and malignant (M) tumors. Materials and Methods: This …
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NEW ADVANCES IN QUANTITATIVE RADIOLOGY: RADIOMICS IN NEURORADIOLOGY APPLIED TO PRIMARY BRAIN TUMORS USING A MACHINE LEARNING APPROACH
Arterial spin labelling (ASL) radiomics analysis to predict IDH mutation and MGMT methylation status in gliomas Fabio M. Doniselli1,2, Riccardo Pascuzzo1, Eleonora Bruno3, Domenico Aquino1, Mattia Verri, Alberto Redolfi, Valeria Cuccarini1, Marco Moscatelli1,2, Maria Grazia Bruzzone1, Luca Maria …
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Detecting and Evaluating Therapy Induced Changes In Radiomics Features Measured From Non-Small Cell Lung Cancer to Predict Patient Outcomes
… purpose of this study was to investigate whether radiomics features measured from weekly 4-dimensional computed tomography (4DCT) images of non-small cell lung cancers (NSCLC) change during treatment and if those changes are prognostic for patient outcomes or dependent on treatment modality. …
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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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Combination of CT-based Radiomics Features and Clinical Data for Predicting Tumor Genetic Profile in patients with Intrahepatic Cholangiocarcinoma
… features were added. Conclusion: CT-based radiomics offers a reliable, non-invasive method for predicting genetic alterations in iCCA, with potential implications for personalized treatment strategies.
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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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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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Computational imaging and multiomic biomarkers for precision medicine: characterizing heterogeneity in lung cancer.
… multiomic phenotypes, formed by integration of radiomics, radiological and pathological information of the patients, enhanced precision in progression-free survival prediction upon combination with prognostic clinical variables. To our knowledge, our study is the first to construct a “multiomic …
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Quantitative Imaging For Precision Medicine In Head and Neck Cancer Patients
… survival using computed tomography (CT)-based radiomics, and overall survival using positron emission tomography (PET)-based radiomics. From DCE-MRI, where T1-weighted images are serially acquired after injection of contrast, quantitative measures of diffusion can be obtained from the series of …
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