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Classification of computerized tomography images to diagnose non-small cell lung cancer using a hybrid model
Lung cancer arises from the abnormal and uncontrolled reproduction of parenchymal cells. Among all cancer cases, lung cancer is one of the prevailing...
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A CNN Transfer Learning-Based Automated Diagnosis of COVID-19 From Lung Computerized Tomography Scan Slices
Lung abnormality is becoming the most widespread illness in individuals of the entire age group. This ailment can occur because of several causes....
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A new step size rule for the superiorization method and its application in computerized tomography
In this paper, we consider a regularized least squares problem subject to convex constraints. Our algorithm is based on the superiorization...
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Using Convolutional Neural Networks for Classifying COVID-19 in Computerized Tomography Scans
COVID-19 is an infectious disease caused by a severe acute respiratory syndrome. The disease has spread rapidly around the world and can lead to...
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Tomography Reconstruction Based on Null Space Search
The paper introduces a new tomography reconstruction approach for gray and binary image reconstruction. The proposed method intends to find a...
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A Deep Learning Framework for Removing Bias from Single-Photon Emission Computerized Tomography
After being photographed by medical equipment, noise in the unprocessed medical image is removed through manual processing and correction to create a...
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A Generalization Study of Automatic Pericardial Segmentation in Computed Tomography Images
The pericardium is a thin membrane sac that covers the heart. As such, the segmentation of the pericardium in computed tomography (CT) can have...
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Computed tomography simulation projection acquisition method of artistic relics based on voxel model
By acquiring the CT (Computed Tomography) simulation projection images of artistic relics, the visual expression ability of artistic relics is...
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A Classification Algorithm for Anomaly Detection in Terahertz Tomography
Terahertz tomography represents an emerging field in the area of nondestructive testing. Detecting outliers in measurements that are caused by...
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Adoption of computerized tomography images in detection of lung nodules and analysis of neuropeptide correlative substances under deep learning algorithm
To solve the problems of low sensitivity and high false positive rate of current lung nodule detection technology, and to explore the correlation...
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An Intelligent Tool to Support Diagnosis of Covid-19 by Texture Analysis of Computerized Tomography X-ray Images and Machine Learning
In December 2019, a member of the Coronaviridae family crossed the barriers between species and hit humans for the first time. Associated with Severe...
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Graph Laplacian and Neural Networks for Inverse Problems in Imaging: GraphLaNet
In imaging problems, the graph Laplacian is proven to be a very effective regularization operator when a good approximation of the image to restore...
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Computerized segmentation of MR brain tumor: an integrated approach of multi-modal fusion and unsupervised clustering
Tumor detection and diagnosis have become topical subjects in the current age. In this paper, an innovative technique for segmenting brain tumor is...
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Performance evaluation of various deep learning based models for effective glaucoma evaluation using optical coherence tomography images
Glaucoma is the dominant reason for irreversible blindness worldwide, and its best remedy is early and timely detection. Optical coherence tomography...
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Organ segmentation from computed tomography images using the 3D convolutional neural network: a systematic review
Computed tomography images are scans that combine a series of X-rays with computer processing techniques to display organs in the body. Recently, 3D...
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Combining Reconstruction and Edge Detection in Computed Tomography
We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of...
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Motion Compensation Strategies in Tomography
Imaging modalities have been developed and established as important and powerful tools to recover characteristics of the interior structure of a...
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Auto Machine Learning Based on Genetic Programming for Medical Image Classification
Medical imaging classification is an area that has taken relevance in recent years due to the capability to support the medical specialist at the...
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Enhancement Sushisen algorithms in Images analysis Technologies to increase computerized tomography images
Contrary to one of the major problems in computer tomography image analysis, Image enhancement can be used to improve the clarity and quality of the...
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Deep Learning Based Lung Nodules Detection from Computer Tomography Images
Lung cancer is among the dominant cause of deaths due to cancer. Lung cancer survival largely depends on the stage at which it is diagnosed with...