AI Medical Compendium Topic

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X-Rays

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Fully automated unified prognosis of Covid-19 chest X-ray/CT scan images using Deep Covix-Net model.

Computers in biology and medicine
SARS-COV2 (Covid-19) prevails in the form of multiple mutant variants causing pandemic situations around the world. Thus, medical diagnosis is not accurate. Although several clinical diagnostic methodologies have been introduced hitherto, chest X-ray...

Coronavirus disease analysis using chest X-ray images and a novel deep convolutional neural network.

Photodiagnosis and photodynamic therapy
BACKGROUND: The recent emergence of a highly infectious and contagious respiratory viral disease known as COVID-19 has vastly impacted human lives and overloaded the health care system. Therefore, it is crucial to develop a fast and accurate diagnost...

Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images.

Computers in biology and medicine
Chest X-ray images are used in deep convolutional neural networks for the detection of COVID-19, the greatest human challenge of the 21st century. Robustness to noise and improvement of generalization are the major challenges in designing these netwo...

Automatic Detection of Covid-19 with Bidirectional LSTM Network Using Deep Features Extracted from Chest X-ray Images.

Interdisciplinary sciences, computational life sciences
Coronavirus disease, which comes up in China at the end of 2019 and showed different symptoms in people infected, affected millions of people. Computer-aided expert systems are needed due to the inadequacy of the reverse transcription-polymerase chai...

2D-3D reconstruction of distal forearm bone from actual X-ray images of the wrist using convolutional neural networks.

Scientific reports
The purpose of the study was to develop a deep learning network for estimating and constructing highly accurate 3D bone models directly from actual X-ray images and to verify its accuracy. The data used were 173 computed tomography (CT) images and 10...

Application of deep learning to identify COVID-19 infection in posteroanterior chest X-rays.

Clinical imaging
INTRODUCTION: The objective of this study was to assess seven configurations of six convolutional deep neural network architectures for classification of chest X-rays (CXRs) as COVID-19 positive or negative.

Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports.

Journal of healthcare engineering
METHODS: We used EHR data of patients included in the Second Manifestations of ARTerial disease (SMART) study. We propose a deep learning-based multimodal architecture for our text mining pipeline that integrates neural text representation with prepr...

Automated Vertebral Segmentation and Measurement of Vertebral Compression Ratio Based on Deep Learning in X-Ray Images.

Journal of digital imaging
Vertebral compression fracture is a deformity of vertebral bodies found on lateral spine images. To diagnose vertebral compression fracture, accurate measurement of vertebral compression ratio is required. Therefore, rapid and accurate segmentation o...

Deep learning applied to automatic disease detection using chest X-rays.

Journal of medical imaging and radiation oncology
Deep learning (DL) has shown rapid advancement and considerable promise when applied to the automatic detection of diseases using CXRs. This is important given the widespread use of CXRs across the world in diagnosing significant pathologies, and the...

4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection.

IEEE transactions on neural networks and learning systems
Due to the high availability of large-scale annotated image datasets, knowledge transfer from pretrained models showed outstanding performance in medical image classification. However, building a robust image classification model for datasets with da...