Nabil Ibtehaz, M. Sohel Rahman
In recent years Deep Learning has brought about a breakthrough in Medical Image Segmentation. In this regard, U-Net has been the most popular architecture in the medical imaging community. Despite outstanding overall performance in segmenting multimodal medical images, through extensive experimentat...
Anas Tahir, Muhammad E. H. Chowdhury, Amith Khandakar, Tawsifur Rahman et al.
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic imaging has become a necessity for screening and monitoring the disease. Numerous...
Yazan Qiblawey, Anas Tahir, Muhammad E. H. Chowdhury, Amith Khandakar et al.
Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients. In this study, a cascaded system is proposed to segment the lung, detect, localize, and quantify COVID-19 infections from computed tomography images. An extensive set of experiments were performed using E...
Nabil Ibtehaz, Sakib Mahmud, Muhammad E. H. Chowdhury, Amith Khandakar et al.
Cardiovascular diseases are one of the most severe causes of mortality, annually taking a heavy toll on lives worldwide. Continuous monitoring of blood pressure seems to be the most viable option, but this demands an invasive process, introducing several layers of complexities and reliability concer...
Md. Salman Shamil, Farhanaz Farheen, Nabil Ibtehaz, Irtesam Mahmud Khan et al.
The coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted non-pharmaceutical interventions (NPI) to slow down the spread. This study proposes an agent-based model that simulates the spread of COVID-19 among the inhabitants of a city. The agent-base...
Sakib Mahmud, Nabil Ibtehaz, Amith Khandakar, Anas Tahir et al.
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 other parameters are required. Several invasive and non-invasive methods have been developed for this purpose. Most exis...
Sakib Mahmud, Nabil Ibtehaz, Amith Khandakar, M. Sohel Rahman et al.
Nabil Ibtehaz, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kıranyaz et al.
In recent years, physiological signal-based authentication has shown great promises, for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most widely studied biosignal, has also received the highest level of attention in this regard. It has been proven with numerous...
Nabil Ibtehaz, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kıranyaz et al.
Abstract Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of Raman spectrum in various fields like medical diagnosis, forensics, m...
Tawsifur Rahman, Amith Khandakar, Md Enamul Hoque, Nabil Ibtehaz et al.
The coronavirus disease 2019 (COVID-19) after outbreaking in Wuhan increasingly spread throughout the world. Fast, reliable, and easily accessible clinical assessment of the severity of the disease can help in allocating and prioritizing resources to reduce mortality. The objective of the study was ...
Arafat Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Anas Tahir et al.
Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital challenges present in the deployment of EEG-based biometrics, which is stable and c...
Nabil Ibtehaz, Mohammad Saifur Rahman, M. Sohel Rahman
Ventricular Fibrillation (VF), one of the most dangerous arrhythmias, is responsible for sudden cardiac arrests. Thus, various algorithms have been developed to predict VF from electrocardiogram (ECG), which is a binary classification problem. In the literature, we find a number of algorithms based ...
Farhanaz Farheen, Md. Salman Shamil, Nabil Ibtehaz, M. Sohel Rahman
Lung cancer is a leading cause of death throughout the world. Because the prompt diagnosis of tumors allows oncologists to discern their nature, type, and mode of treatment, tumor detection and segmentation from CT scan images is a crucial field of study. This paper investigates lung tumor segmentat...
Iram Tazim Hoque, Nabil Ibtehaz, Saumitra Chakravarty, Md. Saifur Rahman et al.
Abstract Background Segmentation of nuclei in cervical cytology pap smear images is a crucial stage in automated cervical cancer screening. The task itself is challenging due to the presence of cervical cells with spurious edges, overlapping cells, neutrophils, and artifacts. Methods After the initi...
Satter Abdus, Nabil Ibtehaz
A Cyber-Physical System strongly depends on the sensor data to understand the current condition of the environment and act on that. Due to network faults, insufficient power supply, and rough environment, sensor data become noisy and the system may perform unwanted operations causing severe damage. ...