136 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Qatar UniversityQA11 papers
- Tampere UniversityFI5 papers
- Weill Cornell Medical College in QatarQA3 papers
- University of DhakaBD2 papers
- Weill Cornell MedicineUS2 papers
- Cornell UniversityUS1 paper
- Hamad bin Khalifa UniversityQA1 paper
- King's College LondonGB1 paper
- Majmaah UniversitySA1 paper
- Newcastle UniversityGB1 paper
- Prince Sattam Bin Abdulaziz UniversitySA1 paper
- Resonance Research (United States)US1 paper
13 papers
FASL-Seg: Anatomy and Tool Segmentation of Surgical Scenes
Muraam Abdel-Ghani, Mahmoud Ali, Mohamed Ali +4
The growing popularity of robotic minimally invasive surgeries has made deep learning-based surgical training a key area of research. A thorough understanding of the surgical scene…
CLIP-RL: Surgical Scene Segmentation Using Contrastive Language-Vision Pretraining & Reinforcement Learning
Fatmaelzahraa Ali Ahmed, Muhammad Arsalan, Abdulaziz Al-Ali +2
Understanding surgical scenes can provide better healthcare quality for patients, especially with the vast amount of video data that is generated during MIS. Processing these video…
Machine-agnostic Automated Lumbar MRI Segmentation using a Cascaded Model Based on Generative Neurons
Promit Basak, Rusab Sarmun, Saidul Kabir +5
Automated lumbar spine segmentation is very crucial for modern diagnosis systems. In this study, we introduce a novel machine-agnostic approach for segmenting lumbar vertebrae and…
Deep Learning for Surgical Instrument Recognition and Segmentation in Robotic-Assisted Surgeries: A Systematic Review
Fatimaelzahraa Ali Ahmed, Mahmoud Yousef, Mariam Ali Ahmed +7
Applying deep learning (DL) for annotating surgical instruments in robot-assisted minimally invasive surgeries (MIS) represents a significant advancement in surgical technology. Th…
Deep learning in computed tomography pulmonary angiography imaging: a dual-pronged approach for pulmonary embolism detection
Fabiha Bushra, Muhammad E. H. Chowdhury, Rusab Sarmun +7
The increasing reliance on Computed Tomography Pulmonary Angiography (CTPA) for Pulmonary Embolism (PE) diagnosis presents challenges and a pressing need for improved diagnostic so…
R2C-GAN: Restore-to-Classify Generative Adversarial Networks for Blind X-Ray Restoration and COVID-19 Classification
Mete Ahishali, Aysen Degerli, Serkan Kiranyaz +3
Restoration of poor quality images with a blended set of artifacts plays a vital role for a reliable diagnosis. Existing studies have focused on specific restoration problems such…
Early Myocardial Infarction Detection over Multi-view Echocardiography
Aysen Degerli, Serkan Kiranyaz, Tahir Hamid +2
Myocardial infarction (MI) is the leading cause of mortality in the world that occurs due to a blockage of the coronary arteries feeding the myocardium. An early diagnosis of MI an…
Fully Automated 2D and 3D Convolutional Neural Networks Pipeline for Video Segmentation and Myocardial Infarction Detection in Echocardiography
Oumaima Hamila, Sheela Ramanna, Christopher J. Henry +4
Cardiac imaging known as echocardiography is a non-invasive tool utilized to produce data including images and videos, which cardiologists use to diagnose cardiac abnormalities in…
Early Detection of Myocardial Infarction in Low-Quality Echocardiography
Aysen Degerli, Morteza Zabihi, Serkan Kiranyaz +4
Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health problem worldwide from which 32.4 million people suffer each year. Early diagnosis and t…
COVID-19 Infection Map Generation and Detection from Chest X-Ray Images
Aysen Degerli, Mete Ahishali, Mehmet Yamac +6
Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numer…
Advance Warning Methodologies for COVID-19 using Chest X-Ray Images
Mete Ahishali, Aysen Degerli, Mehmet Yamac +6
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning…
The Qatar Genome: A Population-Specific Tool for Precision Medicine in the Middle East
Khalid A. Fakhro, Michelle R. Staudt, Monica Denise Ramstetter +14
Reaching the full potential of precision medicine depends on the quality of personalized genome interpretation. In order to facilitate precision medicine in regions of the Middle E…
Mechanisms underlying different onset patterns of focal seizures
Yujiang Wang, Andrew J Trevelyan, Antonio Valentin +3
Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied i…