93 citations · 250 across the 11 of their papers we have counts for
11 papers
Blind ECG Restoration by Operational Cycle-GANs
Serkan Kiranyaz, Ozer Can Devecioglu, Turker Ince +8
Continuous long-term monitoring of electrocardiography (ECG) signals is crucial for the early detection of cardiac abnormalities such as arrhythmia. Non-clinical ECG recordings acq…
A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals
Sakib Mahmud, Nabil Ibtehaz, Amith Khandakar +7
Cardiovascular diseases are the most common causes of death around the world. To detect and treat heart-related diseases, continuous Blood Pressure (BP) monitoring along with many…
Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks
Moncef Gabbouj, Serkan Kiranyaz, Junaid Malik +5
Although numerous R-peak detectors have been proposed in the literature, their robustness and performance levels may significantly deteriorate in low-quality and noisy signals acqu…
COVID-19 Infection Localization and Severity Grading from Chest X-ray Images
Anas M. Tahir, Muhammad E. H. Chowdhury, Amith Khandakar +11
Coronavirus disease 2019 (COVID-19) has been the main agenda of the whole world, since it came into sight in December 2019 as it has significantly affected the world economy and he…
Detection and severity classification of COVID-19 in CT images using deep learning
Yazan Qiblawey, Anas Tahir, Muhammad E. H. Chowdhury +7
Since the breakout of coronavirus disease (COVID-19), the computer-aided diagnosis has become a necessity to prevent the spread of the virus. Detecting COVID-19 at an early stage i…
EDITH :ECG biometrics aided by Deep learning for reliable Individual auTHentication
Nabil Ibtehaz, Muhammad E. H. Chowdhury, Amith Khandakar +5
In recent years, physiological signal based authentication has shown great promises,for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most wide…
Robust R-Peak Detection in Low-Quality Holter ECGs using 1D Convolutional Neural Network
Muhammad Uzair Zahid, Serkan Kiranyaz, Turker Ince +5
Noise and low quality of ECG signals acquired from Holter or wearable devices deteriorate the accuracy and robustness of R-peak detection algorithms. This paper presents a generic…
Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays Images
Tawsifur Rahman, Amith Khandakar, Yazan Qiblawey +8
The use of computer-aided diagnosis in the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandem…
Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-Ray Images
Anas Tahir, Yazan Qiblawey, Amith Khandakar +6
Novel Coronavirus disease (COVID-19) is an extremely contagious and quickly spreading Coronavirus infestation. Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory…
PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms using Fully Convolutional Neural Networks
Nabil Ibtehaz, Sakib Mahmud, Muhammad E. H. Chowdhury +4
Cardiovascular diseases are one of the most severe causes of mortality, taking a heavy toll of lives annually throughout the world. The continuous monitoring of blood pressure seem…
Real-time PCG Anomaly Detection by Adaptive 1D Convolutional Neural Networks
Serkan Kiranyaz, Morteza Zabihi, Ali Bahrami Rad +4
The heart sound signals (Phonocardiogram - PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnosti…