Publications (13)
Fully automated deep learning based segmentation of normal, infarcted and edema regions from multiple cardiac MRI sequences
Xiaoran Zhang, Michelle Noga, Kumaradevan Punithakumar
Myocardial characterization is essential for patients with myocardial infarction and other myocardial diseases, and the assessment is often performed using cardiac magnetic resonan…
Fully Automated Left Atrium Segmentation from Anatomical Cine Long-axis MRI Sequences using Deep Convolutional Neural Network with Unscented Kalman Filter
Xiaoran Zhang, Michelle Noga, David Glynn Martin +1
This study proposes a fully automated approach for the left atrial segmentation from routine cine long-axis cardiac magnetic resonance image sequences using deep convolutional neur…
Accelerated 3D-3D rigid registration of echocardiographic images obtained from apical window using particle filter
Thanuja Uruththirakodeeswaran, Harald Becher, Michelle Noga +4
The perfect alignment of 3D echocardiographic images captured from various angles has improved image quality and broadened the field of view. This study proposes an accelerated seq…
A New Semi-Automated Algorithm for Volumetric Segmentation of the Left Ventricle in Temporal 3D Echocardiography Sequences
Deepa Krishnaswamy, Abhilash R. Hareendranathan, Tan Suwatanaviroj +4
Purpose: Echocardiography is commonly used as a non-invasive imaging tool in clinical practice for the assessment of cardiac function. However, delineation of the left ventricle is…
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge
Gongning Luo, Kuanquan Wang, Jun Liu +27
Efficient automatic segmentation of multi-level (i.e. main and branch) pulmonary arteries (PA) in CTPA images plays a significant role in clinical applications. However, most exist…
Neural Implicit Surface Reconstruction of Freehand 3D Ultrasound Volume with Geometric Constraints
Hongbo Chen, Logiraj Kumaralingam, Shuhang Zhang +9
Three-dimensional (3D) freehand ultrasound (US) is a widely used imaging modality that allows non-invasive imaging of medical anatomy without radiation exposure. Surface reconstruc…
Unsupervised diffeomorphic cardiac image registration using parameterization of the deformation field
Ameneh Sheikhjafari, Deepa Krishnaswamy, Michelle Noga +2
This study proposes an end-to-end unsupervised diffeomorphic deformable registration framework based on moving mesh parameterization. Using this parameterization, a deformation fie…
ISLES'24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand?
Ezequiel de la Rosa, Ruisheng Su, Mauricio Reyes +37
Accurate estimation of brain infarction (i.e., irreversibly damaged tissue) is critical for guiding treatment decisions in acute ischemic stroke. Reliable infarct prediction inform…
MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images
Lei Li, Fuping Wu, Sihan Wang +29
Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardiu…
A systematic review on the role of artificial intelligence in sonographic diagnosis of thyroid cancer: Past, present and future
Fatemeh Abdolali, Atefeh Shahroudnejad, Abhilash Rakkunedeth Hareendranathan +3
Thyroid cancer is common worldwide, with a rapid increase in prevalence across North America in recent years. While most patients present with palpable nodules through physical exa…
A training-free recursive multiresolution framework for diffeomorphic deformable image registration
Ameneh Sheikhjafari, Michelle Noga, Kumaradevan Punithakumar +1
Diffeomorphic deformable image registration is one of the crucial tasks in medical image analysis, which aims to find a unique transformation while preserving the topology and inve…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…