AIMC Topic: Lung

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Fine-Tuning U-Net for Ultrasound Image Segmentation: Different Layers, Different Outcomes.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 24, 2020
One way of resolving the problem of scarce and expensive data in deep learning for medical applications is using transfer learning and fine-tuning a network which has been trained on a large data set. The common practice in transfer learning is to ke...
Humans Machine Learning Lung Ultrasonography Image Processing, Computer-Assisted
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Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation.

Sensors (Basel, Switzerland) Nov 24, 2020
Several pathologies have a direct impact on society, causing public health problems. Pulmonary diseases such as Chronic obstructive pulmonary disease (COPD) are already the third leading cause of death in the world, leaving tuberculosis at ninth with...
Internet of Things Tomography, X-Ray Computed Lung Deep Learning Image Processing, Computer-Assisted
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Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering Nov 23, 2020
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...
SARS-CoV-2 Sensitivity and Specificity COVID-19 Humans Radiographic Image Interpretation, Computer-Assisted Databases, Factual Lung Machine Learning Early Diagnosis Reproducibility of Results Software Radiography, Thoracic
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Automatic detection of COVID-19 from chest radiographs using deep learning.

Radiography (London, England : 1995) Nov 11, 2020
INTRODUCTION: The breakdown of a deadly infectious disease caused by a newly discovered coronavirus (named SARS n-CoV2) back in December 2019 has shown no respite to slow or stop in general. This contagious disease has spread across different lengths...
Coronavirus Infections Radiography, Thoracic Bronchi SARS-CoV-2 Lung Deep Learning Humans Pandemics
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CT-ORG, a new dataset for multiple organ segmentation in computed tomography.

Scientific data Nov 11, 2020
Despite the relative ease of locating organs in the human body, automated organ segmentation has been hindered by the scarcity of labeled training data. Due to the tedium of labeling organ boundaries, most datasets are limited to either a small numbe...
Urinary Bladder Fourier Analysis Kidney Liver Bone and Bones Lung Imaging, Three-Dimensional Image Processing, Computer-Assisted Humans Brain Tomography, X-Ray Computed Neural Networks, Computer Algorithms
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Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Nature communications Nov 6, 2020
Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that...
Deep Learning Image Processing, Computer-Assisted Mice Animals Male Lung Spleen X-Ray Microtomography Whole Body Imaging Animal Structures Kidney Mice, Inbred C57BL Liver Algorithms Brain Female Reproducibility of Results
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Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.

European journal of radiology Nov 4, 2020
INTRODUCTION: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and ...
Tomography, X-Ray Computed Female Humans COVID-19 ROC Curve Middle Aged Radiographic Image Interpretation, Computer-Assisted Lung Reproducibility of Results Deep Learning Sensitivity and Specificity Male
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The study of automatic machine learning base on radiomics of non-focus area in the first chest CT of different clinical types of COVID-19 pneumonia.

Scientific reports Nov 3, 2020
To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-...
Aged Adult Male Coronavirus Infections Pneumonia, Viral Humans COVID-19 Middle Aged Machine Learning Tomography, X-Ray Computed Lung Pandemics Female
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A bilinear convolutional neural network for lung nodules classification on CT images.

International journal of computer assisted radiology and surgery Nov 2, 2020
PURPOSE: Lung cancer is the most frequent cancer worldwide and is the leading cause of cancer-related deaths. Its early detection and treatment at the stage of a lung nodule improve the prognosis. In this study was proposed a new classification appro...
Lung Diagnosis, Computer-Assisted Lung Neoplasms Humans Neural Networks, Computer Tomography, X-Ray Computed Support Vector Machine Solitary Pulmonary Nodule
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The detection of lung cancer using massive artificial neural network based on soft tissue technique.

BMC medical informatics and decision making Oct 31, 2020
BACKGROUND: A proposed computer aided detection (CAD) scheme faces major issues during subtle nodule recognition. However, radiologists have not noticed subtle nodules in beginning stage of lung cancer while a proposed CAD scheme recognizes non subtl...
Sensitivity and Specificity Lung Lung Neoplasms Humans Neural Networks, Computer Solitary Pulmonary Nodule Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Image Interpretation, Computer-Assisted
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