74 citations · 262 across the 80 of their papers we have counts for
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Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion
Zahra Karimaghaloo, Dumitru Fetco, Haz-Edine Assemlal +2
Accurate longitudinal analysis of brain MRI is often hindered by evolving lesions, which bias automated neuroimaging pipelines. While deep generative models have shown promise in i…
DINOMotion: advanced robust tissue motion tracking with DINOv2 in 2D-Cine MRI-guided radiotherapy
Soorena Salari, Catherine Spino, Laurie-Anne Pharand +4
Accurate tissue motion tracking is critical to ensure treatment outcome and safety in 2D-Cine MRI-guided radiotherapy. This is typically achieved by registration of sequential imag…
Weakly Supervised Intracranial Aneurysm Detection and Segmentation in MR angiography via Multi-task UNet with Vesselness Prior
Erin Rainville, Amirhossein Rasoulian, Hassan Rivaz +1
Intracranial aneurysms (IAs) are abnormal dilations of cerebral blood vessels that, if ruptured, can lead to life-threatening consequences. However, their small size and soft contr…
Lightweight Physics-Aware Zero-Shot Ultrasound Plane-Wave Denoising
Hojat Asgariandehkordi, Mostafa Sharifzadeh, Morteza Rezanejad +1
Ultrasound Coherent Plane-Wave Compounding (CPWC) enhances image contrast by combining echoes from multiple steered transmissions. While increasing the number of steering angles ge…
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…
CABLD: Contrast-Agnostic Brain Landmark Detection with Consistency-Based Regularization
Soorena Salari, Arash Harirpoush, Hassan Rivaz +1
Anatomical landmark detection in medical images is essential for various clinical and research applications, including disease diagnosis and surgical planning. However, manual land…
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…
Denoising Plane Wave Ultrasound Images Using Diffusion Probabilistic Models
Hojat Asgariandehkordi, Sobhan Goudarzi, Mostafa Sharifzadeh +2
Ultrasound plane wave imaging is a cutting-edge technique that enables high frame-rate imaging. However, one challenge associated with high frame-rate ultrasound imaging is the hig…
Vim4Path: Self-Supervised Vision Mamba for Histopathology Images
Ali Nasiri-Sarvi, Vincent Quoc-Huy Trinh, Hassan Rivaz +1
Representation learning from Gigapixel Whole Slide Images (WSI) poses a significant challenge in computational pathology due to the complicated nature of tissue structures and the…
Joint enhancement of automatic chest X-ray diagnosis and radiological gaze prediction with multi-stage cooperative learning
Zirui Qiu, Hassan Rivaz, Yiming Xiao
Purpose: As visual inspection is an inherent process during radiological screening, the associated eye gaze data can provide valuable insights into relevant clinical decisions. As…
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…
VesselShot: Few-shot learning for cerebral blood vessel segmentation
Mumu Aktar, Hassan Rivaz, Marta Kersten-Oertel +1
Angiography is widely used to detect, diagnose, and treat cerebrovascular diseases. While numerous techniques have been proposed to segment the vascular network from different imag…
Robust RF Data Normalization for Deep Learning
Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz
Radio frequency (RF) data contain richer information compared to other data types, such as envelope or B-mode, and employing RF data for training deep neural networks has attracted…
Frequency-Space Prediction Filtering for Phase Aberration Correction in Plane-Wave Ultrasound
Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz
Ultrasound imaging often suffers from image degradation stemming from phase aberration, which represents a significant contributing factor to the overall image degradation in ultra…
Dense Error Map Estimation for MRI-Ultrasound Registration in Brain Tumor Surgery Using Swin UNETR
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz +1
Early surgical treatment of brain tumors is crucial in reducing patient mortality rates. However, brain tissue deformation (called brain shift) occurs during the surgery, rendering…
Deformable-Detection Transformer for Microbubble Localization in Ultrasound Localization Microscopy
Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz
To overcome the half a wavelength resolution limitations of ultrasound imaging, microbubbles (MBs) have been utilized widely in the field. Conventional MB localization methods are…
How inter-rater variability relates to aleatoric and epistemic uncertainty: a case study with deep learning-based paraspinal muscle segmentation
Parinaz Roshanzamir, Hassan Rivaz, Joshua Ahn +6
Recent developments in deep learning (DL) techniques have led to great performance improvement in medical image segmentation tasks, especially with the latest Transformer model and…
Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to-Aberration Approach
Mostafa Sharifzadeh, Sobhan Goudarzi, An Tang +2
One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which…
FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgery
Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz +1
In brain tumor resection, accurate removal of cancerous tissues while preserving eloquent regions is crucial to the safety and outcomes of the treatment. However, intra-operative t…
Deep Ultrasound Denoising Using Diffusion Probabilistic Models
Hojat Asgariandehkordi, Sobhan Goudarzi, Adrian Basarab +1
Ultrasound images are widespread in medical diagnosis for musculoskeletal, cardiac, and obstetrical imaging due to the efficiency and non-invasiveness of the acquisition methodolog…
Exploiting Mechanics-Based Priors for Lateral Displacement Estimation in Ultrasound Elastography
Md Ashikuzzaman, Ali K. Z. Tehrani, Hassan Rivaz
Tracking the displacement between the pre- and post-deformed radio-frequency (RF) frames is a pivotal step of ultrasound elastography, which depicts tissue mechanical properties to…
Phase Aberration Correction without Reference Data: An Adaptive Mixed Loss Deep Learning Approach
Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz
Phase aberration is one of the primary sources of image quality degradation in ultrasound, which is induced by spatial variations in sound speed across the heterogeneous medium. Th…
Lateral Strain Imaging using Self-supervised and Physically Inspired Constraints in Unsupervised Regularized Elastography
Ali K. Z. Tehrani, Md Ashikuzzaman, Hassan Rivaz
Convolutional Neural Networks (CNN) have shown promising results for displacement estimation in UltraSound Elastography (USE). Many modifications have been proposed to improve the…