1 code implementation • 20 Jun 2022 • Xiaodan Xing, Jiahao Huang, Yang Nan, Yinzhe Wu, Chengjia Wang, Zhifan Gao, Simon Walsh, Guang Yang
The destitution of image data and corresponding expert annotations limit the training capacities of AI diagnostic models and potentially inhibit their performance.
no code implementations • 7 Mar 2022 • Chengjia Wang, Guang Yang, Giorgos Papanastasiou
Moreover, inverse-consistency is a fundamental inter-modality registration property that is not considered in deep learning registration algorithms.
no code implementations • 9 Dec 2021 • Qinghao Ye, Yuan Gao, Weiping Ding, Zhangming Niu, Chengjia Wang, Yinghui Jiang, Minhao Wang, Evandro Fei Fang, Wade Menpes-Smith, Jun Xia, Guang Yang
The multi-domain shift problem for the multi-center and multi-scanner studies is therefore nontrivial that is also crucial for a dependable recognition and critical for reproducible and objective diagnosis and prognosis.
1 code implementation • 5 Sep 2020 • Haochuan Jiang, Chengjia Wang, Agisilaos Chartsias, Sotirios A. Tsaftaris
Together with the corresponding encoding features, these representations are propagated to decoding layers with U-Net skip-connections.
no code implementations • 5 Aug 2020 • Jingyu Hao, Chengjia Wang, Heye Zhang, Guang Yang
In particular, the generator uses different training strategies to generate multiple offspring and retain the best.
no code implementations • 23 Jun 2020 • Yifeng Guo, Chengjia Wang, Heye Zhang, Guang Yang
The performance of traditional compressive sensing-based MRI (CS-MRI) reconstruction is affected by its slow iterative procedure and noise-induced artefacts.
no code implementations • 1 May 2020 • Ming Li, Chengjia Wang, Heye Zhang, Guang Yang
In addition, for a better interpretation of pathophysiological processes, clinical decision-making and prognosis, such cardiac anatomy segmentation and quantitative analysis of various clinical indices should ideally be performed for the data covering the full cardiac cycle.
1 code implementation • 4 Dec 2019 • Tian Xia, Agisilaos Chartsias, Chengjia Wang, Sotirios A. Tsaftaris
Our method synthesises images conditioned on two factors: age (a continuous variable), and status of Alzheimer's Disease (AD, an ordinal variable).
2 code implementations • 11 Nov 2019 • Agisilaos Chartsias, Giorgos Papanastasiou, Chengjia Wang, Scott Semple, David E. Newby, Rohan Dharmakumar, Sotirios A. Tsaftaris
Core to our method is learning a disentangled decomposition into anatomical and imaging factors.
no code implementations • 24 Jul 2019 • Ming Li, Weiwei Zhang, Guang Yang, Chengjia Wang, Heye Zhang, Huafeng Liu, Wei Zheng, Shuo Li
Our method is built as an end-to-end framework for segmentation and classification.
no code implementations • 11 Jul 2019 • Chengjia Wang, Giorgos Papanastasiou, Agisilaos Chartsias, Grzegorz Jacenkow, Sotirios A. Tsaftaris, Heye Zhang
Inter-modality image registration is an critical preprocessing step for many applications within the routine clinical pathway.
no code implementations • 21 Feb 2019 • Xiahai Zhuang, Lei LI, Christian Payer, Darko Stern, Martin Urschler, Mattias P. Heinrich, Julien Oster, Chunliang Wang, Orjan Smedby, Cheng Bian, Xin Yang, Pheng-Ann Heng, Aliasghar Mortazi, Ulas Bagci, Guanyu Yang, Chenchen Sun, Gaetan Galisot, Jean-Yves Ramel, Thierry Brouard, Qianqian Tong, Weixin Si, Xiangyun Liao, Guodong Zeng, Zenglin Shi, Guoyan Zheng, Chengjia Wang, Tom MacGillivray, David Newby, Kawal Rhode, Sebastien Ourselin, Raad Mohiaddin, Jennifer Keegan, David Firmin, Guang Yang
This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017.
no code implementations • 12 Aug 2018 • Chengjia Wang, Gillian Macnaught, Giorgos Papanastasiou, Tom MacGillivray, David Newby
Recently, the cycle-consistent generative adversarial networks (CycleGAN) has been widely used for synthesis of multi-domain medical images.
no code implementations • 12 Apr 2018 • Chengjia Wang, Tom MacGillivray, Gillian Macnaught, Guang Yang, David Newby
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.
no code implementations • 20 Mar 2018 • Chengjia Wang, Keith A. Goatman, James Boardman, Erin Beveridge, David Newby, Scott Semple
In this paper we describe improvements to the particle swarm optimizer (PSO) made by inclusion of an unscented Kalman filter to guide particle motion.