A wavelet-based deep learning pipeline for efficient COVID-19 diagnosis via CT slices
O Attallah, A Samir - Applied Soft Computing, 2022 - Elsevier
The quick diagnosis of the novel coronavirus (COVID-19) disease is vital to prevent its
propagation and improve therapeutic outcomes. Computed tomography (CT) is believed to …
propagation and improve therapeutic outcomes. Computed tomography (CT) is believed to …
A deep learning and handcrafted based computationally intelligent technique for effective COVID-19 detection from X-ray/CT-scan imaging
The world has witnessed dramatic changes because of the advent of COVID19 in the last
few days of 2019. During the last more than two years, COVID-19 has badly affected the …
few days of 2019. During the last more than two years, COVID-19 has badly affected the …
WRANet: wavelet integrated residual attention U-Net network for medical image segmentation
Medical image segmentation is crucial for the diagnosis and analysis of disease. Deep
convolutional neural network methods have achieved great success in medical image …
convolutional neural network methods have achieved great success in medical image …
Enhanced detonators detection in X-ray baggage inspection by image manipulation and deep convolutional neural networks
Detecting detonators is a challenging task because they can be easily mis-classified as
being a harmless organic mass, especially in high baggage throughput scenarios. Of …
being a harmless organic mass, especially in high baggage throughput scenarios. Of …
A wavelet and local binary pattern-based feature descriptor for the detection of chronic infection through thoracic X-ray images
This investigation attempts to propose a novel Wavelet and Local Binary Pattern-based
Xception feature Descriptor (WLBPXD) framework, which uses a deep-learning model for …
Xception feature Descriptor (WLBPXD) framework, which uses a deep-learning model for …
Coronavirus disease identification using Multi-subband feature analysis in DWT domain
Coronavirus disease early identification and differentiating it with other lung infections is a
complex and time-consuming task. At present RT-PCR and Antigen tests are used for …
complex and time-consuming task. At present RT-PCR and Antigen tests are used for …
Comparative study of DCNN and image processing based classification of chest X-rays for identification of COVID-19 patients using fine-tuning
The conventional detection of COVID-19 by evaluating the CT scan images is tiresome,
often experiences high inter-observer variability and uncertainty issues. This work proposes …
often experiences high inter-observer variability and uncertainty issues. This work proposes …
Development of an AI-based FSA for real-time condition monitoring for industrial machine
Automated continuous condition monitoring of industrial electrical machines to identify
internal faults has become one of the critical research areas for the past decade. Among …
internal faults has become one of the critical research areas for the past decade. Among …
EVALUATION OF THE EFFECTS OF LUNGS CHEST X-RAY IMAGE FUSION WITH ITS WAVELET SCATTERING TRANSFORM COEFFICIENTS ON THE …
R Arvanaghi, S Meshgini - Biomedical Engineering: Applications …, 2023 - World Scientific
Background and Objective: Regarding the Coronavirus disease-2019 (COVID-19) pandemic
in past years and using medical images to detect it, the image processing of the lungs and …
in past years and using medical images to detect it, the image processing of the lungs and …
Amalgamation of wavelet transform and neural network for COVID-19 detection
A zoonotic natured virus affecting almost every part of the globe is COVID-19. Early
detection of such disease may lead to curable affairs. Since then, many research institutes …
detection of such disease may lead to curable affairs. Since then, many research institutes …