15 citations · 47 across the 10 of their papers we have counts for
11 papers
Which Pretext Task Transfers? Self-Supervised Pretraining Objectives for Lung Ultrasound
Moein Heidari, Junbo Rao, Jai Choraria +3
Self-supervised learning (SSL) can reduce the need for labelled medical images, but the choice of pretext objective remains unclear for lung ultrasound (LUS). Contrastive learning,…
Echo-ENet: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation
Moein Heidari, Afshin Bozorgpour, AmirHossein Zarif-Fakharnia +6
Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements requires manual delineation at end-dias…
A Study on the Performance of U-Net Modifications in Retroperitoneal Tumor Segmentation
Moein Heidari, Ehsan Khodapanah Aghdam, Alexander Manzella +5
The retroperitoneum hosts a variety of tumors, including rare benign and malignant types, which pose diagnostic and treatment challenges due to their infrequency and proximity to v…
Multi-Scale Feature Fusion using Parallel-Attention Block for COVID-19 Chest X-ray Diagnosis
Xiao Qi, David J. Foran, John L. Nosher +1
Under the global COVID-19 crisis, accurate diagnosis of COVID-19 from Chest X-ray (CXR) images is critical. To reduce intra- and inter-observer variability, during the radiological…
Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis
Xiao Qi, David J. Foran, John L. Nosher +1
The role of chest X-ray (CXR) imaging, due to being more cost-effective, widely available, and having a faster acquisition time compared to CT, has evolved during the COVID-19 pand…
Realistic Ultrasound Image Synthesis for Improved Classification of Liver Disease
Hui Che, Sumana Ramanathan, David Foran +3
With the success of deep learning-based methods applied in medical image analysis, convolutional neural networks (CNNs) have been investigated for classifying liver disease from ul…
Multi-Feature Semi-Supervised Learning for COVID-19 Diagnosis from Chest X-ray Images
Xiao Qi, John L. Nosher, David J. Foran +1
Computed tomography (CT) and chest X-ray (CXR) have been the two dominant imaging modalities deployed for improved management of Coronavirus disease 2019 (COVID-19). Due to faster…
Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network
Xiao Qi, Lloyd Brown, David J. Foran +1
Recently, the outbreak of the novel Coronavirus disease 2019 (COVID-19) pandemic has seriously endangered human health and life. Due to limited availability of test kits, the need…
Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images
Jian Ren, Ilker Hacihaliloglu, Eric A. Singer +2
Automatic and accurate Gleason grading of histopathology tissue slides is crucial for prostate cancer diagnosis, treatment, and prognosis. Usually, histopathology tissue slides fro…
Factorized Adversarial Networks for Unsupervised Domain Adaptation
Jian Ren, Jianchao Yang, Ning Xu +1
In this paper, we propose Factorized Adversarial Networks (FAN) to solve unsupervised domain adaptation problems for image classification tasks. Our networks map the data distribut…
EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching from Scratch
Jian Ren, Zhe Li, Jianchao Yang +3
Designing the structure of neural networks is considered one of the most challenging tasks in deep learning, especially when there is few prior knowledge about the task domain. In…