activity
20182023
most citedA two-stage 3D Unet framework for multi-class segmentation on full resolution image

62 citations · 102 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2023★ 1 cited

An open-source deep learning algorithm for efficient and fully-automatic analysis of the choroid in optical coherence tomography

Jamie Burke, Justin Engelmann, Charlene Hamid +9

Purpose: To develop an open-source, fully-automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We used…

q-bio.QM2023

Evaluation of an automated choroid segmentation algorithm in a longitudinal kidney donor and recipient cohort

Jamie Burke, Dan Pugh, Tariq Farrah +7

Purpose: To evaluate the performance of an automated choroid segmentation algorithm in optical coherence tomography (OCT) data using a longitudinal kidney donor and recipient cohor…

eess.IV2019

Automated Segmentation of Optical Coherence Tomography Angiography Images: Benchmark Data and Clinically Relevant Metrics

Ylenia Giarratano, Eleonora Bianchi, Calum Gray +4

Optical coherence tomography angiography (OCTA) is a novel non-invasive imaging modality for the visualisation of microvasculature in vivo that has encountered broad adoption in re…

cs.CV2019★ 29 cited

Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge

Xiahai Zhuang, Lei Li, Christian Payer +31

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable…

cs.CV2018★ 3 cited

Unsupervised learning for cross-domain medical image synthesis using deformation invariant cycle consistency networks

Chengjia Wang, Gillian Macnaught, Giorgos Papanastasiou +2

Recently, the cycle-consistent generative adversarial networks (CycleGAN) has been widely used for synthesis of multi-domain medical images. The domain-specific nonlinear deformati…

cs.CV2018★ 62 cited

A two-stage 3D Unet framework for multi-class segmentation on full resolution image

Chengjia Wang, Tom MacGillivray, Gillian Macnaught +2

Deep convolutional neural networks (CNNs) have been intensively used for multi-class segmentation of data from different modalities and achieved state-of-the-art performances. Howe…