activity
20172022
most citedFully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI

58 citations · 202 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2022

Dual-stream spatiotemporal networks with feature sharing for monitoring animals in the home cage

Ezechukwu I. Nwokedi, Rasneer S. Bains, Luc Bidaut +3

This paper presents a spatiotemporal deep learning approach for mouse behavioural classification in the home-cage. Using a series of dual-stream architectures with assorted modific…

cs.CV2021★ 2 cited

Unsupervised detection of mouse behavioural anomalies using two-stream convolutional autoencoders

Ezechukwu I Nwokedi, Rasneer S Bains, Luc Bidaut +3

This paper explores the application of unsupervised learning to detecting anomalies in mouse video data. The two models presented in this paper are a dual-stream, 3D convolutional…

eess.IV2020★ 30 cited

DR-Unet104 for Multimodal MRI brain tumor segmentation

Jordan Colman, Lei Zhang, Wenting Duan +1

In this paper we propose a 2D deep residual Unet with 104 convolutional layers (DR-Unet104) for lesion segmentation in brain MRIs. We make multiple additions to the Unet architectu…

eess.IV2020★ 2 cited

Automated Segmentation of Left Ventricle in 2D echocardiography using deep learning

Neda Azarmehr, Xujiong Ye, Faraz Janan +3

Following the successful application of the U-Net to medical images, there have been different encoder-decoder models proposed as an improvement to the original U-Net for segmentin…

cs.CV2019★ 18 cited

MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks

Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +3

In this paper, we propose a novel learning based method for automated segmentation of brain tumor in multimodal MRI images, which incorporates two sets of machine -learned and hand…

cs.CY2019★ 24 cited

A hybrid model for predicting human physical activity status from lifelogging data

Ji Ni, Bowei Chen, Nigel M. Allinson +1

One trend in the recent healthcare transformations is people are encouraged to monitor and manage their health based on their daily diets and physical activity habits. However, muc…

cs.CV2018★ 13 cited

Automatic individual pig detection and tracking in surveillance videos

Lei Zhang, Helen Gray, Xujiong Ye +2

Individual pig detection and tracking is an important requirement in many video-based pig monitoring applications. However, it still remains a challenging task in complex scenes, d…

cs.CV2017★ 58 cited

Fully Automatic Segmentation and Objective Assessment of Atrial Scars for Longstanding Persistent Atrial Fibrillation Patients Using Late Gadolinium-Enhanced MRI

Guang Yang, Xiahai Zhuang, Habib Khan +10

Purpose: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is correlated with increased morbidity and mortality. It is associated with atrial fibrosis, which may b…

cs.CV2017★ 44 cited

Deep De-Aliasing for Fast Compressive Sensing MRI

Simiao Yu, Hao Dong, Guang Yang +8

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clinical applications in order to reduce the scanning cost and improve the patient experience. This can also pote…

cs.CV2017★ 11 cited

Multimodal MRI brain tumor segmentation using random forests with features learned from fully convolutional neural network

Mohammadreza Soltaninejad, Lei Zhang, Tryphon Lambrou +2

In this paper, we propose a novel learning based method for automated segmenta-tion of brain tumor in multimodal MRI images. The machine learned features from fully convolutional n…