Search Results for author: Hassan Rivaz

Found 56 papers, 5 papers with code

Vim4Path: Self-Supervised Vision Mamba for Histopathology Images

1 code implementation20 Apr 2024 Ali Nasiri-Sarvi, Vincent Quoc-Huy Trinh, Hassan Rivaz, Mahdi S. Hosseini

Multi-instance learning methods have addressed this challenge, leveraging image patches to classify slides utilizing pretrained models using Self-Supervised Learning (SSL) approaches.

Representation Learning Self-Supervised Learning +1

MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image Segmentation

no code implementations29 Mar 2024 Taha Koleilat, Hojat Asgariandehkordi, Hassan Rivaz, Yiming Xiao

Medical image segmentation of anatomical structures and pathology is crucial in modern clinical diagnosis, disease study, and treatment planning.

Image Segmentation Medical Image Segmentation +3

Joint chest X-ray diagnosis and clinical visual attention prediction with multi-stage cooperative learning: enhancing interpretability

no code implementations25 Mar 2024 Zirui Qiu, Hassan Rivaz, Yiming Xiao

As deep learning has become the state-of-the-art for computer-assisted diagnosis, interpretability of the automatic decisions is crucial for clinical deployment.

Contrastive Learning Multi-Task Learning

Is visual explanation with Grad-CAM more reliable for deeper neural networks? a case study with automatic pneumothorax diagnosis

no code implementations29 Aug 2023 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 the credence of these methods for safer and quicker clinical adoption.

Decision Making

Phase Aberration Correction: A Deep Learning-Based Aberration to Aberration Approach

no code implementations22 Aug 2023 Mostafa Sharifzadeh, Sobhan Goudarzi, An Tang, Habib Benali, Hassan Rivaz

This dataset serves to mitigate the data scarcity problem in the development of deep learning-based techniques for phase aberration correction.

Robust RF Data Normalization for Deep Learning

no code implementations22 Aug 2023 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 growing interest in ultrasound image processing.

Frequency-Space Prediction Filtering for Phase Aberration Correction in Plane-Wave Ultrasound

no code implementations22 Aug 2023 Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz

In this study, we illustrate the challenge of applying this technique to plane-wave imaging, where, at shallower depths, signals from more distant elements lose relevance, and a fewer number of elements contribute to image reconstruction.

Image Reconstruction

FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgery

no code implementations26 Jul 2023 Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz, Yiming Xiao

In brain tumor resection, accurate removal of cancerous tissues while preserving eloquent regions is crucial to the safety and outcomes of the treatment.

Towards multi-modal anatomical landmark detection for ultrasound-guided brain tumor resection with contrastive learning

no code implementations26 Jul 2023 Soorena Salari, Amirhossein Rasoulian, Hassan Rivaz, Yiming Xiao

Specifically, two convolutional neural networks were trained jointly to encode image features in MRI and US scans to help match the US image patch that contain the corresponding landmarks in the MRI.

Contrastive Learning Image Registration

Deep Ultrasound Denoising Using Diffusion Probabilistic Models

no code implementations12 Jun 2023 Hojat Asgariandehkordi, Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz

To improve the Peak Signal to Noise Ratio (PSNR) of the images, previous denoising methods often remove the speckles, which could be informative for radiologists and also for quantitative ultrasound.

Denoising Medical Diagnosis

Exploiting Mechanics-Based Priors for Lateral Displacement Estimation in Ultrasound Elastography

no code implementations31 May 2023 Md Ashikuzzaman, Ali K. Z. Tehrani, Hassan Rivaz

This paper proposes exploiting the effective Poisson's ratio (EPR)-based mechanical correspondence between the axial and lateral strains along with the RF data fidelity and displacement continuity to improve the lateral displacement and strain estimation accuracies.

Phase Aberration Correction without Reference Data: An Adaptive Mixed Loss Deep Learning Approach

no code implementations10 Mar 2023 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.

Lateral Strain Imaging using Self-supervised and Physically Inspired Constraints in Unsupervised Regularized Elastography

no code implementations16 Dec 2022 Ali K. Z. Tehrani, Md Ashikuzzaman, Hassan Rivaz

Many modifications have been proposed to improve the displacement estimation of CNNs for USE in the axial direction.

Infusing known operators in convolutional neural networks for lateral strain imaging in ultrasound elastography

no code implementations31 Oct 2022 Ali K. Z. Tehrani, Hassan Rivaz

This method took into account the range of the feasible lateral strain defined by the rules of physics of motion and employed a regularization strategy to improve the lateral strains.

Transformer-Based Microbubble Localization

no code implementations23 Sep 2022 Sepideh K. Gharamaleki, Brandon Helfield, Hassan Rivaz

Ultrasound Localization Microscopy (ULM) is an emerging technique that employs the localization of echogenic microbubbles (MBs) to finely sample and image the microcirculation beyond the diffraction limit of ultrasound imaging.

Object Recognition Transfer Learning

Analytic Optimization-Based Microbubble Tracking in Ultrasound Super-Resolution Microscopy

no code implementations21 Sep 2022 Md Ashikuzzaman, Brandon Helfield, Hassan Rivaz

Ultrasound localization microscopy (ULM) refers to a promising medical imaging modality that systematically leverages the advantages of contrast-enhanced ultrasound (CEUS) to surpass the diffraction barrier and delineate the microvascular map.

Position Super-Resolution

DiffeoRaptor: Diffeomorphic Inter-modal Image Registration using RaPTOR

1 code implementation12 Sep 2022 Nima Masoumi, Hassan Rivaz, M. Omair Ahmad, Yiming Xiao

Results: The proposed algorithm, named DiffeoRaptor, was validated with three public databases for the tasks of brain and abdominal image registration while comparing the results against three state-of-the-art techniques, including FLASH, NiftyReg, and Symmetric image normalization (SyN).

Image Registration

Physics-Inspired Regularized Pulse-Echo Quantitative Ultrasound: Efficient Optimization with ADMM

no code implementations13 Aug 2022 Noushin Jafarpisheh, Laura Castaneda Martinez, Hayley Whitson, Ivan M. Rosado-Mendez, Hassan Rivaz

Pulse-echo Quantitative ultrasound (PEQUS), which estimates the quantitative properties of tissue microstructure, entails estimating the average attenuation and the backscatter coefficient (BSC).

Inverse Problem of Ultrasound Beamforming with Denoising-Based Regularized Solutions

1 code implementation16 Jun 2022 Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz

During the past few years, inverse problem formulations of ultrasound beamforming have attracted a growing interest.


Deep Estimation of Speckle Statistics Parametric Images

no code implementations8 Jun 2022 Ali K. Z. Tehrani, Ivan M. Rosado-Mendez, Hassan Rivaz

Quantitative Ultrasound (QUS) provides important information about the tissue properties.

Multi-Task Learning

Physically Inspired Constraint for Unsupervised Regularized Ultrasound Elastography

no code implementations5 Jun 2022 Ali K. Z. Tehrani, Hassan Rivaz

Recently, the architecture of the optical flow networks has been modified to be able to use RF data.

Optical Flow Estimation

Incorporating Gradient Similarity for Robust Time Delay Estimation in Ultrasound Elastography

no code implementations30 Mar 2022 Md Ashikuzzaman, Timothy J. Hall, Hassan Rivaz

The data term associated with the existing techniques takes only the amplitude similarity into account and hence is not sufficiently robust to the outlier samples present in the RF frames under consideration.

Bi-Directional Semi-Supervised Training of Convolutional Neural Networks for Ultrasound Elastography Displacement Estimation

no code implementations31 Jan 2022 Ali K. Z. Tehrani, Mostafa Sharifzadeh, Emad Boctor, Hassan Rivaz

We also show that the network fine-tuned by our proposed method using experimental phantom data performs well on in vivo data similar to the network fine-tuned on in vivo data.

Optical Flow Estimation Transfer Learning

Robust Scatterer Number Density Segmentation of Ultrasound Images

no code implementations16 Jan 2022 Ali K. Z. Tehrani, Ivan M. Rosado-Mendez, Hassan Rivaz

In conventional methods, the envelope data is divided into small overlapping windows (a strategy here we refer to as patching), and statistical parameters such as SNR and skewness are employed to classify each patch of envelope data.

Domain Adaptation Multi-Task Learning

Ultrasound Strain Imaging using ADMM

no code implementations12 Jan 2022 Md Ashikuzzaman, Hassan Rivaz

ADMM empowers the proposed algorithm to use different techniques for optimizing different parts of the cost function and obtain high-contrast strain images with smooth background and sharp boundaries.

Deep Ultrasound Denoising Without Clean Data

no code implementations7 Jan 2022 Sobhan Goudarzi, Hassan Rivaz

On one hand, the transmitted ultrasound beam gets attenuated as propagates through the tissue.


Second-Order Ultrasound Elastography with L1-norm Spatial Regularization

no code implementations6 Jan 2022 Md Ashikuzzaman, Hassan Rivaz

To resolve these issues, herein, we propose a novel TDE algorithm where instead of L2-, L1-norms of both first- and second-order displacement derivatives are taken into account to devise the continuity functional.

Time Series Analysis

A Unifying Approach to Inverse Problems of Ultrasound Beamforming and Deconvolution

no code implementations28 Dec 2021 Sobhan Goudarzi, Adrian Basarab, Hassan Rivaz

In parallel to beamforming approaches, deconvolution methods have also been explored in ultrasound imaging to mitigate the adverse effects of PSF.

Image Reconstruction

Vision Transformer for Classification of Breast Ultrasound Images

no code implementations27 Oct 2021 Behnaz Gheflati, Hassan Rivaz

In the past decade, convolutional neural networks (CNNs) have emerged as the method of choice in vision applications and have shown excellent potential in automatic classification of US images.


Fast Strain Estimation and Frame Selection in Ultrasound Elastography using Machine Learning

no code implementations16 Oct 2021 Abdelrahman Zayed, Hassan Rivaz

In the inference stage, we use dynamic programming (DP) to compute an initial displacement estimate of around 1% of the samples, and then decompose this sparse displacement into a linear combination of the 12 displacement modes.

BIG-bench Machine Learning Position

Plane-Wave Ultrasound Beamforming: A Deep Learning Approach

no code implementations27 Sep 2021 Sobhan Goudarzi, Hassan Rivaz

Simulation test results confirm that the proposed method reconstructs images with a high quality in terms of resolution and contrast, which are also visually similar to the proposed ground-truth image.

An Ultra-Fast Method for Simulation of Realistic Ultrasound Images

no code implementations21 Sep 2021 Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz

Convolutional neural networks (CNNs) have attracted a rapidly growing interest in a variety of different processing tasks in the medical ultrasound community.

Data Augmentation Lesion Segmentation

Estimation of the Scatterer Size Distributions in Quantitative Ultrasound Using Constrained Optimization

no code implementations21 Sep 2021 Noushin Jafarpisheh, Ivan M. Rosado-Mendez, Timothy J. Hall, Hassan Rivaz

In the first technique, we cast scatterer size distribution as an optimization problem, and efficiently solve it using a linear system of equations.

Ultrasound Domain Adaptation Using Frequency Domain Analysis

no code implementations21 Sep 2021 Mostafa Sharifzadeh, Ali K. Z. Tehrani, Habib Benali, Hassan Rivaz

A common issue in exploiting simulated ultrasound data for training neural networks is the domain shift problem, where the trained models on synthetic data are not generalizable to clinical data.

Domain Adaptation Lesion Segmentation

Automatic 3D Ultrasound Segmentation of Uterus Using Deep Learning

no code implementations20 Sep 2021 Bahareh Behboodi, Hassan Rivaz, Susan Lalondrelle, Emma Harris

In the second scenario, our proposed network was trained using all the planes of each 3D volume.


Explainable AI and susceptibility to adversarial attacks: a case study in classification of breast ultrasound images

no code implementations9 Aug 2021 Hamza Rasaee, Hassan Rivaz

Ultrasound is a non-invasive imaging modality that can be conveniently used to classify suspicious breast nodules and potentially detect the onset of breast cancer.

Decision Making Multi-Task Learning +1

Investigating Shift-Variance of Convolutional Neural Networks in Ultrasound Image Segmentation

1 code implementation22 Jul 2021 Mostafa Sharifzadeh, Habib Benali, Hassan Rivaz

To the best of our knowledge, this problem has not been studied in ultrasound image segmentation or even more broadly in ultrasound images.

Data Augmentation Image Segmentation +2

Common Limitations of Image Processing Metrics: A Picture Story

1 code implementation12 Apr 2021 Annika Reinke, Minu D. Tizabi, Carole H. Sudre, Matthias Eisenmann, Tim Rädsch, Michael Baumgartner, Laura Acion, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, Matthew Blaschko, Florian Buettner, M. Jorge Cardoso, Jianxu Chen, Veronika Cheplygina, Evangelia Christodoulou, Beth Cimini, Gary S. Collins, Sandy Engelhardt, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Fred Hamprecht, Daniel A. Hashimoto, Doreen Heckmann-Nötzel, Peter Hirsch, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, A. Emre Kavur, Hannes Kenngott, Jens Kleesiek, Andreas Kleppe, Sven Kohler, Florian Kofler, Annette Kopp-Schneider, Thijs Kooi, Michal Kozubek, Anna Kreshuk, Tahsin Kurc, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern Menze, David Moher, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, M. Alican Noyan, Jens Petersen, Gorkem Polat, Susanne M. Rafelski, Nasir Rajpoot, Mauricio Reyes, Nicola Rieke, Michael Riegler, Hassan Rivaz, Julio Saez-Rodriguez, Clara I. Sánchez, Julien Schroeter, Anindo Saha, M. Alper Selver, Lalith Sharan, Shravya Shetty, Maarten van Smeden, Bram Stieltjes, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul Jäger, Lena Maier-Hein

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation.

Instance Segmentation object-detection +2

Fast and Robust Localization of Surgical Array using Kalman Filter

no code implementations22 Dec 2020 Md Ashikuzzaman, Noushin Jafarpisheh, Sunil Rottoo, Pierre Brisson, Hassan Rivaz

This paper introduces a fast and computationally efficient implementation of linear KF to improve the measurement accuracy of an optical tracking system with high temporal resolution.


Virtual Source Synthetic Aperture for Accurate Lateral Displacement Estimation in Ultrasound Elastography

no code implementations19 Dec 2020 Morteza Mirzaei, Amir Asif, Hassan Rivaz

Despite capabilities of elastography techniques in estimating displacement in both axial and lateral directions, estimation of axial displacement is more accurate than lateral direction due to higher sampling frequency, higher resolution and having a carrier signal propagating in the axial direction.

Semi-Supervised Training of Optical Flow Convolutional Neural Networks in Ultrasound Elastography

no code implementations2 Jul 2020 Ali K. Z. Tehrani, Morteza Mirzaei, Hassan Rivaz

Convolutional Neural Networks (CNN) have been found to have great potential in optical flow problems thanks to an abundance of data available for training a deep network.

Image and Video Processing

Fine tuning U-Net for ultrasound image segmentation: which layers?

no code implementations19 Feb 2020 Mina Amiri, Rupert Brooks, Hassan Rivaz

In this study, we investigated the effect of fine-tuning different layers of a U-Net which was trained on segmentation of natural images in breast ultrasound image segmentation.

Image Segmentation Segmentation +1

Automatic Frame Selection using CNN in Ultrasound Elastography

no code implementations17 Feb 2020 Abdelrahman Zayed, Guy Cloutier, Hassan Rivaz

Ultrasound elastography is used to estimate the mechanical properties of the tissue by monitoring its response to an internal or external force.

Breast lesion segmentation in ultrasound images with limited annotated data

no code implementations21 Jan 2020 Bahareh Behboodi, Mina Amiri, Rupert Brooks, Hassan Rivaz

Ultrasound (US) is one of the most commonly used imaging modalities in both diagnosis and surgical interventions due to its low-cost, safety, and non-invasive characteristic.

Image Segmentation Lesion Segmentation +2

Automatic Frame Selection Using MLP Neural Network in Ultrasound Elastography

no code implementations13 Nov 2019 Abdelrahman Zayed, Hassan Rivaz

This work focuses on strain imaging in quasi-static elastography, where the tissue undergoes slow deformations and strain images are estimated as a surrogate for elasticity modulus.

Fast Approximate Time-Delay Estimation in Ultrasound Elastography Using Principal Component Analysis

no code implementations13 Nov 2019 Abdelrahman Zayed, Hassan Rivaz

Time delay estimation (TDE) is a critical and challenging step in all ultrasound elastography methods.

Ultrasound segmentation using U-Net: learning from simulated data and testing on real data

no code implementations24 Apr 2019 Bahareh Behboodi, Hassan Rivaz

Therefore, in this study, we propose the use of simulated ultrasound (US) images for training the U-Net deep learning segmentation architecture and test on tissue-mimicking phantom data collected by an ultrasound machine.


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