no code implementations • 7 Jul 2020 • Hang Min, Darryl McClymont, Shekhar S. Chandra, Stuart Crozier, Andrew P. Bradley
Breast lesions are firstly extracted as region candidates using the novel 3D multiscale morphological sifting (MMS).
no code implementations • 27 Nov 2020 • Siyu Liu, Jason A. Dowling, Craig Engstrom, Peter B. Greer, Stuart Crozier, Shekhar S. Chandra
In this work, we propose Manifold Disentanglement Generative Adversarial Network (MDGAN), a novel image translation framework that explicitly models these two types of features.
no code implementations • 31 Mar 2021 • Xinwen Liu, Jing Wang, Fangfang Tang, Shekhar S. Chandra, Feng Liu, Stuart Crozier
MRI images of the same subject in different contrasts contain shared information, such as the anatomical structure.
no code implementations • 1 Jun 2021 • Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun
Method: A recently proposed deep learning-based QSM method, namely xQSM, is investigated to assess the accuracy of dipole inversion on reduced brain coverages.
no code implementations • 2 Aug 2021 • Jacob M. White, Stuart Crozier, Shekhar S. Chandra
Sampling strategies are important for sparse imaging methodologies, especially those employing the discrete Fourier transform (DFT).
no code implementations • 12 Sep 2021 • Wei Dai, Boyeong Woo, Siyu Liu, Matthew Marques, Craig B. Engstrom, Peter B. Greer, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra
Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under investigation.
no code implementations • 6 Dec 2021 • Jessica M. Bugeja, Ying Xia, Shekhar S. Chandra, Nicholas J. Murphy, Jillian Eyles, Libby Spiers, Stuart Crozier, David J. Hunter, Jurgen Fripp, Craig Engstrom
Automated analyses of 3D MR images from patients with FAI using the CamMorph pipeline showed that, in comparison with female patients, male patients had significantly greater cam volume, surface area and height.
no code implementations • 22 Sep 2022 • Siyu Liu, Linfeng Liu, Xuan Vinh, Stuart Crozier, Craig Engstrom, Fatima Nasrallah, Shekhar Chandra
DiDiGAN learns a disease manifold of AD and CN visual characteristics, and the style codes sampled from this manifold are imposed onto an anatomical structural "blueprint" to synthesise paired AD and CN magnetic resonance images (MRIs).
1 code implementation • 17 Mar 2021 • Yang Gao, Martijn Cloos, Feng Liu, Stuart Crozier, G. Bruce Pike, Hongfu Sun
In this study, a learning-based Deep Complex Residual Network (DCRNet) is proposed to recover both the magnitude and phase images from incoherently undersampled data, enabling high acceleration of QSM acquisition.
1 code implementation • 30 Nov 2022 • Boyeong Woo, Craig Engstrom, William Baresic, Jurgen Fripp, Stuart Crozier, Shekhar S. Chandra
A second anomaly-aware network, which was compared to anomaly-na\"ive segmentation networks, was used to provide a final automated segmentation of the femoral, tibial and patellar bones and cartilages from the knee MR images containing a spectrum of bone anomalies.
1 code implementation • 28 Jun 2020 • Siyu Liu, Wei Dai, Craig Engstrom, Jurgen Fripp, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra
However, medical image datasets have diverse-sized images and features, and developing a model simultaneously for multiple datasets is challenging.
1 code implementation • 28 Jun 2019 • Hang Min, Devin Wilson, Yinhuang Huang, Siyu Liu, Stuart Crozier, Andrew P. Bradley, Shekhar S. Chandra
We propose a fully-integrated computer-aided detection (CAD) system for simultaneous mammographic mass detection and segmentation without user intervention.
1 code implementation • 14 Apr 2020 • Yang Gao, Xuanyu Zhu, Stuart Crozier, Feng Liu, Hongfu Sun
Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications.
Image and Video Processing
2 code implementations • 15 Nov 2021 • Yang Gao, Zhuang Xiong, Amir Fazlollahi, Peter J Nestor, Viktor Vegh, Fatima Nasrallah, Craig Winter, G. Bruce Pike, Stuart Crozier, Feng Liu, Hongfu Sun
In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the novel neural networks.
1 code implementation • 6 Apr 2022 • Xuanyu Zhu, Yang Gao, Feng Liu, Stuart Crozier, Hongfu Sun
The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects.