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Efficient Chest X-Ray Investigation Using Firefly Algorithm Optimized Deep and Handcrafted Features
Radiological imaging of the chest (X-ray) is a cost-effective, widely accepted method of examining the lungs and abnormalities. During this research,...
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Impact of image enhancement methods on lung disease diagnosis using x-ray images
Nowadays, Lung disease is the most common and fatal disease around the world. It causes patients to experience shortening of breath, fever, and...
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Denoising techniques for cephalometric x-ray images: A comprehensive review
Noising in X-ray imaging has been one of the biggest challenges that leads to insufficient and improper diagnosis. Despite the fact that X-rays are...
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2D/3D Shape Model Registration with X-ray Images for Patient-Specific Spine Geometry Reconstruction
The use of preoperative CT and intraoperative fluoroscopic-guided surgical robotic assistance for spinal disease treatment has gained significant...
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Joint Edge-Guided and Spectral Transformation Network for Self-supervised X-Ray Image Restoration
X-rays are widely utilized in the security inspection field due to their ability to penetrate objects and visualize intricate details and structural...
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Interpretable Deep Learning Model for Tuberculosis Detection Using X-Ray Images
Tuberculosis (TB) is a worldwide severe health concern that causes numerous deaths yearly. Detecting TB promptly and precisely is crucial for...
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Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis
Automated diagnosis prediction from medical images is a valuable resource to support clinical decision-making. However, such systems usually need to...
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Chest X-ray Image Super-Resolution via Deep Contrast Consistent Feature Network
This paper proposes a chest X-ray image super-resolution reconstruction method - Deep Contrast Consistent Feature Network, which articulates the...
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A Patient-Specific Self-supervised Model for Automatic X-Ray/CT Registration
The accurate estimation of X-ray source pose in relation to pre-operative images is crucial for minimally invasive procedures. However, existing deep...
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Automatic lung disease classification from the chest X-ray images using hybrid deep learning algorithm
The chest X-ray images provide vital information about the congestion cost-effectively. We propose a novel Hybrid Deep Learning Algorithm (HDLA)...
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Lightweight deep learning methods for panoramic dental X-ray image segmentation
Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight...
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Computer Vision for X-Ray Testing Imaging, Systems, Image Databases, and Algorithms
[FIRST EDITION] This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray...
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Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Images
With the development of remote X-ray detection for Corona Virus Disease 2019 (COVID-19), the quantized block compressive sensing technology plays an...
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Hard X-Ray Emission in Solar Flares
In this chapter we provide an overview of the solar flare phenomenon with particular emphasis on aspects that can be best investigated through X-ray...
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Beyond Model Accuracy: Identifying Hidden Underlying Issues in Chest X-ray Classification
As deep learning model performance continues to advance in detecting and classifying disease, it is important to show that these models are...
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Triplet Learning for Chest X-Ray Image Search in Automated COVID-19 Analysis
Chest radiology images such as CT scans and X-ray images have been extensively employed in computer-assisted analysis of COVID-19, utilizing various...
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Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis
While recent advances in large-scale foundational computer vision models show promising results, their application to the medical domain has not yet...
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Brain tumor X-ray images enhancement and classification using anisotropic diffusion filter and transfer learning models
One of the diseases with the fastest rate of spread is brain tumors, which affect millions of people. Thus, brain tumor classification is intensively...
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Anomaly Guided Generalizable Super-Resolution of Chest X-Ray Images Using Multi-level Information Rendering
Single image super-resolution (SISR) methods aim to generate a high-resolution image from the corresponding low-resolution images. Such methods may...
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Learning from ambiguous labels for X-Ray security inspection via weakly supervised correction
X-ray security inspection has been dominated by supervised learning detectors for several years. The extreme angles, overlap** occlusion, and...
