Guang-Zhong Yang
Imperial College London
979Publications
55H-index
14.6kCitations
Publications 979
Newest
Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 6.13
Yulei Qin , Juan Wen + 6 AuthorsGuang-Zhong Yang55
Estimated H-index: 55
Chromosome classification is critical for karyotyping in abnormality diagnosis. To expedite diagnosis process, we present a novel method named Varifocal-Net for simultaneous classification of chromosome's type and polarity using deep convolutional networks. The approach consists of one global-scale network (G-Net) and one local-scale network (L-Net). It follows two stages. The first stage is to learn both global and local features. We extract global features and detect finer local regions via th...
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Published on Apr 1, 2019 in International Conference on Robotics and Automation
Dandan Zhang (Imperial College London), Bo Xiao5
Estimated H-index: 5
(Imperial College London)
+ 3 AuthorsGuang-Zhong Yang55
Estimated H-index: 55
(Imperial College London)
Master–slave control is a common form of human–robot interaction for robotic surgery. To ensure seamless and intuitive control, a mechanism of self-adaptive motion scaling during teleoperaton is proposed in this letter. The operator can retain precise control when conducting delicate or complex manipulation, while the movement to a remote target is accelerated via adaptive motion scaling. The proposed framework consists of three components: 1) situation awareness, 2) skill level awareness, and 3...
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Published on Apr 1, 2019 in International Conference on Robotics and Automation
Xiao-Yun Zhou2
Estimated H-index: 2
(Imperial College London),
Guang-Zhong Yang55
Estimated H-index: 55
(Imperial College London)
Two-dimensional (2-D) biomedical semantic segmentation is important for robotic vision in surgery. Segmentation methods based on deep convolutional neural network (DCNN) can out-perform conventional methods in terms of both accuracy and levels of automation. One common issue in training a DCNN for biomedical semantic segmentation is the internal covariate shift where the training of convolutional kernels is encumbered by the distribution change of input features, hence both the training speed an...
1 Citations Source Cite
Published on Apr 1, 2019 in International Conference on Robotics and Automation
Gauthier Gras4
Estimated H-index: 4
(Imperial College London),
Guang-Zhong Yang55
Estimated H-index: 55
(Imperial College London)
Current surgical augmented reality (AR) systems typically employ an on-demand display behavior, where the surgeon can toggle the AR on or off using a switch. The need to be able to turn the AR off is in part due to the obstructing nature of AR overlays, potentially hiding important information from the surgeon in order to provide see-through vision. This on-demand paradigm is inefficient as the surgeon is always in one of two sub-optimal states: either they do not benefit at all from the image g...
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Lei Li4
Estimated H-index: 4
,
Fuping Wu + 6 AuthorsXiahai Zhuang14
Estimated H-index: 14
Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to the low image quality. In this work, we propose a fully automated method based on the graph-cuts framework, where the potentials of the graph are learned on a surface mesh of the left atrium (LA) using a multi-scale convolutional neural network (MS-...
Xiahai Zhuang14
Estimated H-index: 14
,
Lei Li4
Estimated H-index: 4
+ 31 AuthorsCheng Bian2
Estimated H-index: 2
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 for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be arduous due to the large variation of the heart shape, and different image qualities of the clinical data. To achieve this goal, a set of training data is generally needed for constructing priors or for tr...
Published on Mar 1, 2019in IEEE Transactions on Medical Imaging 6.13
Yun Gu6
Estimated H-index: 6
,
Khushi Vyas2
Estimated H-index: 2
+ 1 AuthorsGuang-Zhong Yang55
Estimated H-index: 55
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Published on Jan 1, 2019in Biosensors and Bioelectronics 8.17
Bing Li (Imperial College London), Haijie Tan (Imperial College London)+ 3 AuthorsGuang-Zhong Yang55
Estimated H-index: 55
(Imperial College London)
Abstract Nature is a great source of inspiration for the development of solutions for biomedical problems. We present a novel biosensor design utilizing two-photon polymerisation and graphene to fabricate an enhanced biosensing platform for the detection of motile bacteria. A cage comprising venous valve-inspired directional micro-structure is fabricated around graphene-based sensing electronics. The asymmetric 3D micro-structure promotes motile cells to swim from outside the cage towards the in...
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Published on Jan 1, 2019in NeuroImage: Clinical 3.87
Felix Raschke6
Estimated H-index: 6
(Helmholtz-Zentrum Dresden-Rossendorf),
Thomas R. Barrick31
Estimated H-index: 31
(St George's, University of London)
+ 3 AuthorsFranklyn A. Howe50
Estimated H-index: 50
(St George's, University of London)
Abstract Purpose To develop a statistical method of combining multimodal MRI (mMRI) of adult glial brain tumours to generate tissue heterogeneity maps that indicate tumour grade and infiltration margins. Materials and methods We performed a retrospective analysis of mMRI from patients with histological diagnosis of glioma ( n = 25). 1 H Magnetic Resonance Spectroscopic Imaging (MRSI) was used to label regions of “pure” low- or high-grade tumour across image types. Normal brain and oedema charact...
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Published on Jan 1, 2019in IEEE Transactions on Biomedical Engineering 4.29
Yun Gu6
Estimated H-index: 6
,
Mali Shen + 1 AuthorsGuang-Zhong Yang55
Estimated H-index: 55
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