1 code implementation • 22 Oct 2023 • Haoran Wang, Qiuye Jin, Shiman Li, Siyu Liu, Manning Wang, Zhijian Song
Deep learning has achieved widespread success in medical image analysis, leading to an increasing demand for large-scale expert-annotated medical image datasets.
no code implementations • 14 Jul 2023 • Linfeng Liu, Junyan Lyu, Siyu Liu, Xiaoying Tang, Shekhar S. Chandra, Fatima A. Nasrallah
The prediction of mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD) is important for early treatment to prevent or slow the progression of AD.
no code implementations • 11 Apr 2023 • Siyu Liu, Xunyuan Yin, Jinfeng Liu
Multi-layer perceptron (MLP) neural networks capture the dominant dynamics of the process and train the network parameters with low-dimensional data obtained from open-loop simulations.
no code implementations • 14 Mar 2023 • Siyu Liu, Xunyuan Yin, Jinfeng Liu
The sensor selection problem is converted to an optimization problem, and is efficiently solved by a one-by-one removal approach through sensitivity analysis.
no code implementations • 10 Mar 2023 • Wei Dai, Siyu Liu, Craig B. Engstrom, Shekhar S. Chandra
The discriminator is generalised to small domain shifts as much as permissible by the training data, and the generator automatically diversifies the training samples using a manifold of input features learnt during segmentation.
no code implementations • 29 Nov 2022 • Siyu Liu, Marija Ilic
This paper concerns the resilience of systems with wind power upon wind reduction by evaluating the potential of corrective actions, such as generation and load dispatch, on minimizing the effects of transmission line failures.
no code implementations • 2 Nov 2022 • Siyu Liu, Marija Ilic
This paper concerns the potential of corrective actions, such as generation and load dispatch on minimizing the effects of transmission line failures in electric power systems.
no code implementations • 1 Oct 2022 • Linfeng Liu, Siyu Liu, Lu Zhang, Xuan Vinh To, Fatima Nasrallah, Shekhar S. Chandra
The model uses a novel Cascaded Modality Transformer architecture with cross-attention to incorporate multi-modal information for more informed predictions.
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).
no code implementations • 18 Aug 2022 • Linhao Qu, Siyu Liu, Xiaoyu Liu, Manning Wang, Zhijian Song
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of patient prognosis and treatment outcome.
no code implementations • 1 Aug 2022 • Siyu Liu, Xunyuan Yin, Zhichao Pan, Jinfeng Liu
The minimum number of sensors is determined in a way such that the local sensitivity matrix is full column rank.
no code implementations • 10 Jun 2022 • Siyu Liu, Catherine Lu, Sharifa Alghowinem, Lea Gotoh, Cynthia Breazeal, Hae Won Park
The prevalence of suicide has been on the rise since the 20th century, causing severe emotional damage to individuals, families, and communities alike.
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 • 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.
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.
no code implementations • 6 Mar 2020 • Jiwei Jia, Jian Ding, Siyu Liu, Guidong Liao, Jingzhi Li, Ben Duan, Guoqing Wang, Ran Zhang
Home quarantine is the most important one to prevent the spread of COVID-19.
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.