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 53 for “"Chest X-ray"”.
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Chest X-Ray Image Classification with Deep Learning
… considers one essential task in CAD, the chest X-ray (CXR) image classification problem, with the deep learning technologies from the following three aspects. First, considering most diseases existing in CXRs usually happen in small, localized areas, we propose to localize the local …
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Multi-Dimensional Evaluation Metrics for Chest X-Ray Reports
… radiology reports using the large MIMIC-CXR chest x-ray dataset. However, there has been little work focused on evaluating the quality of generated reports from a clinical perspective, where accuracy is the most important factor. Current evaluation metrics evaluate reports in one dimension. …
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Implementation and evaluation of a bony structure suppression software tool for chest X-ray imaging
… algorithm in order to assist in the analysis of chest X-ray images. The diagnosis of pulmonary tuberculosis (TB) often includes the evaluation of chest X-ray images, and the reliability of image interpretation depends upon the experience of the radiologist. Computer-aided diagnosis (CAD) may be …
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The relationship between chest X-ray findings, bacterial load and treatment-related outcomes in persons with extensively drug resistant TB
… There is a paucity of literature describing the chest X-ray (CXR) findings in patients with XDR-TB, and whether disease extent is related to treatment outcomes and the evolution of resistance remains unclear. It has been shown that patients with radiological extensive drug-sensitive TB have …
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The conclusions drawn from ventilation/perfusion single photon emission computed tomography (SPECT) compared to lung perfusion SPECT and a chest x-ray (CXR) in patients with suspected pulmonary pulmonary thromboembolism
… can be safely omitted or replaced by a chest x-ray. These studies were based on planar ventilation perfusion (V/Q) scintigraphy. We evaluated the value of the V single photon emission computed tomography (SPECT) on the final conclusion drawn from a V/Q SPECT and the possible role of the …
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A systematic review: the role of neuroinflammation as a pathway to injury in traumatic brain injury
… tuberculosis has a high mortality. Chest x-rays are an adjunct diagnostic tool for tuberculosis but has high inter-reader variability, which may be reduced with chest x-ray scoring systems. We analysed and scored chest x-rays of hospitalised patients with HIV-associated tuberculosis …
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Pneumonia Detection with Game-Theoretic Rough Sets
… Machine learning has been applied to classify chest X-ray images into pneumonia-positive and pneumonia-negative classes to allow an early diagnosis and support medical experts’ decisions about pneumonia. Nonetheless, the previous attempt focus on binary classification that may not consider the …
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"A-OK": Chest Radiograph During Primary Survey Facilitates Faster, More Accurate Endotracheal Tube Position in Injured Children
… techniques are inaccurate and that early chest x-ray (CXR) would overcome such inaccuracies, allowing for faster intervention of malpositioned ETTs.
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Natural Language Foundation Models in Medical Artificial Intelligence
… useful clinical knowledge, for tasks like chest x-ray interpretation, differential diagnosis, history taking, and clinical management. As a whole, this thesis aims to further our collective understanding of the potential of natural language foundation models in medicine, while emphasizing …
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Improving Lung Cancer Risk Prediction: Integration of Novel Predictors and Modelling Using Machine Learning Random Forest versus the Validated PLCOm2012 Logistic Regression Model
… vitamin A, total isoflavone, and history of chest x-ray also resulted in an increase in ROC-AUC from 0.797 to 0.810 (ΔROC-AUC= 0.013, p<0.001). This study demonstrated that the application of traditional LR exhibited superior predictive performance in comparison to the advanced machine …
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Synthesizing a complete tomographic study with nodules from multiple radiograph views via deep generative models
Chest radiography encodes a 3D anatomy into a complex 2D representation. This projection creates distinctive challenges even for the most experienced radiologists as many critical findings are superimposed, often resulting in error or further imaging. In particular, it is difficult to visualize the …
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ΣΥΜΒΟΛΗ ΣΤΗ ΜΕΛΕΤΗ ΤΗΣ ΣΥΣΤΡΟΦΗΣ ΤΟΥ ΣΤΟΜΑΧΟΥ
… HERNIA, THE DIAGNOSIS CAN BE MADE ON A PLAIN CHEST X-RAY FILM, IF THE CHARACTERISTIC AIR-FLUID LEVELS ARE PRESENT ABOVE AS WELL AS BELOW THE DIAPHRAGM. ACUTE VOLUULUS IS A SURGICAL EMERGENCY (REDUCTION WITH ANTERION GASTROPEXY,GASTRECTOMY OR GASTRENETROANASTOMOSIS ACCORDING TO THE UNDERLYING …
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Generative Adversarial Network (GAN) for Medical Image Synthesis and Augmentation
… cell dataset (19,578 images) and a COVID-19 chest X-ray dataset (2,347 images) to test the new Ad CycleGAN. The quantitative metrics include mean squared error (MSE), root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), universal image quality index (UIQI), spatial correlation …
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Radiological progression of lung disease in Human Immunodeficiency Virus (HIV)-infected children
Introduction: There are limited data on the chest X-ray (CXR) abnormalities in human immunodeficiency virus (HIV)-infected children in low- and middle-income countries (LMIC's). Aim: To investigate the evolution of CXR abnormalities in HIV-infected children in LMIC's, to correlate this with the …
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자발성 종격동 기종의 임상 양상 분석
… was 22.7 ± 13.2 years, and 67 (73.6%) were male. Chest pain (58, 37.2%) was the predominant symptom. The most frequent precipitating factor before developing SPM was the patient’s cough (15.4%), whereas the majority of patients (51, 56.0%) had no precipitating factors. Chest X-ray was diagnostic …
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Computer-assisted detection of lung cancer nudules in medical chest X-rays
… in 1895 with Rontgen's discovery of x-rays. X-ray photography has played a very prominent role in diagnostics of all kinds since then and continues to do so. It is true that more sophisticated and successful medical imaging systems are available. These include Magnetic Resonance Imaging …
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Multimodal Representation Learning for Medical Image Analysis
… learning approaches in the application of chest x-ray analysis.
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Geometric Deep Learning for Healthcare Applications
… Tracking the progression of pathologies in chest radiography poses several challenges in anatomical motion estimation and image registration as this task requires spatially aligning the sequential X-rays and modelling temporal dynamics in change detection. The first part of this thesis …
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Improving Model Generalization of Pneumonia Detection from Chest Xray Images Using Deep Learning and Transfer Learning
… and one of the leading causes of mortality, with chest X-rays serving as the primary diagnostic tool. Despite their promise, deep learning models for pneumonia detection often face limitations in generalization, performing strongly on familiar datasets but losing accuracy when applied to unseen …
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