7 citations · 13 across the 20 of their papers we have counts for
20 papers
Reliability of deep learning models for anatomical landmark detection: The role of inter-rater variability
Soorena Salari, Hassan Rivaz, Yiming Xiao
Automated detection of anatomical landmarks plays a crucial role in many diagnostic and surgical applications. Progresses in deep learning (DL) methods have resulted in significant…
Comparative Analysis of Diffusion Generative Models in Computational Pathology
Denisha Thakkar, Vincent Quoc-Huy Trinh, Sonal Varma +3
Diffusion Generative Models (DGM) have rapidly surfaced as emerging topics in the field of computer vision, garnering significant interest across a wide array of deep learning appl…
Ensemble Learning for Microbubble Localization in Super-Resolution Ultrasound
Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz
Super-resolution ultrasound (SR-US) is a powerful imaging technique for capturing microvasculature and blood flow at high spatial resolution. However, accurate microbubble (MB) loc…
Vision Mamba for Classification of Breast Ultrasound Images
Ali Nasiri-Sarvi, Mahdi S. Hosseini, Hassan Rivaz
Mamba-based models, VMamba and Vim, are a recent family of vision encoders that offer promising performance improvements in many computer vision tasks. This paper compares Mamba-ba…
Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches
Ali K. Z. Tehrani, Guy Cloutier, An Tang +2
Quantitative ultrasound (QUS) analyzes the ultrasound backscattered data to find the properties of scatterers that correlate with the tissue microstructure. Statistics of the envel…
Is visual explanation with Grad-CAM more reliable for deeper neural networks? a case study with automatic pneumothorax diagnosis
Zirui Qiu, Hassan Rivaz, Yiming Xiao
While deep learning techniques have provided the state-of-the-art performance in various clinical tasks, explainability regarding their decision-making process can greatly enhance…