1 code implementation • 6 May 2024 • Xiwen Chen, Peijie Qiu, Wenhui Zhu, Huayu Li, Hao Wang, Aristeidis Sotiras, Yalin Wang, Abolfazl Razi
Deep neural networks, including transformers and convolutional neural networks, have significantly improved multivariate time series classification (MTSC).
no code implementations • 29 Apr 2024 • Zhuofu Pan, Qingkai Sui, Yalin Wang, Jiang Luo, Jie Chen, Hongtian Chen
However, traditional methods exhibit limited effectiveness in modeling high-dimensional nonlinearity and big data, and the decoupling idea has not been well-valued in data-driven frameworks.
no code implementations • 9 Apr 2024 • Yujian Xiong, Yanshuai Tu, Zhong-Lin Lu, Yalin Wang
Human vision has different concentration on visual fields.
no code implementations • 7 Apr 2024 • Yujian Xiong, Wenhui Zhu, Zhong-Lin Lu, Yalin Wang
The reconstruction of human visual inputs from brain activity, particularly through functional Magnetic Resonance Imaging (fMRI), holds promising avenues for unraveling the mechanisms of the human visual system.
no code implementations • 30 Nov 2023 • Zhangsihao Yang, Mingyuan Zhou, Mengyi Shan, Bingbing Wen, Ziwei Xuan, Mitch Hill, Junjie Bai, Guo-Jun Qi, Yalin Wang
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset.
1 code implementation • 31 Oct 2023 • Peijie Qiu, Pan Xiao, Wenhui Zhu, Yalin Wang, Aristeidis Sotiras
In this paper, we proposed a sparsely coded MIL (SC-MIL) that addresses those two aspects at the same time by leveraging sparse dictionary learning.
1 code implementation • 19 Aug 2023 • Wenhui Zhu, Peijie Qiu, Xiwen Chen, Oana M. Dumitrascu, Yalin Wang
Multiple instance learning (MIL) was a weakly supervised learning approach that sought to assign binary class labels to collections of instances known as bags.
Multiple Instance Learning Weakly Supervised Classification +3
2 code implementations • 2 Jun 2023 • Wenhui Zhu, Peijie Qiu, Xiwen Chen, Xin Li, Natasha Lepore, Oana M. Dumitrascu, Yalin Wang
Over the past few decades, convolutional neural networks (CNNs) have been at the forefront of the detection and tracking of various retinal diseases (RD).
no code implementations • 30 May 2023 • Yu Fu, Yanyan Huang, Shunjie Dong, Yalin Wang, Tianbai Yu, Meng Niu, Cheng Zhuo
Deep neural networks (DNN) have been designed to predict the chronological age of a healthy brain from T1-weighted magnetic resonance images (T1 MRIs), and the predicted brain age could serve as a valuable biomarker for the early detection of development-related or aging-related disorders.
no code implementations • 31 Mar 2023 • Jianfeng Wu, Yi Su, Yanxi Chen, Wenhui Zhu, Eric M. Reiman, Richard J. Caselli, Kewei Chen, Paul M. Thompson, Junwen Wang, Yalin Wang
Objective: To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline.
no code implementations • 8 Feb 2023 • Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu, Peijie Qiu, Yalin Wang
Our results show the superiority of our LBO-based convolution layer and adapted pooling over the conventionally used unitary cortical thickness, graph Laplacian, and point cloud representation.
2 code implementations • 6 Feb 2023 • Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Jacob M. Sobczak, Mohammad Farazi, Zhangsihao Yang, Keshav Nandakumar, Yalin Wang
Non-mydriatic retinal color fundus photography (CFP) is widely available due to the advantage of not requiring pupillary dilation, however, is prone to poor quality due to operators, systemic imperfections, or patient-related causes.
1 code implementation • 6 Feb 2023 • Wenhui Zhu, Peijie Qiu, Mohammad Farazi, Keshav Nandakumar, Oana M. Dumitrascu, Yalin Wang
In this paper, we proposed a simple but effective end-to-end framework for enhancing poor-quality retinal fundus images.
no code implementations • 28 Oct 2022 • Jianfeng Wu, Yi Su, Wenhui Zhu, Negar Jalili Mallak, Natasha Lepore, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Kewei Chen, Yalin Wang
Experimental results suggest that amyloid/tau measurements predicted with our PASCP-MP representations are closer to the real values than the measures derived from other approaches, such as hippocampal surface area, volume, and shape morphometry features based on spherical harmonics (SPHARM).
no code implementations • 17 Oct 2022 • Mohammad Farazi, Wenhui Zhu, Zhangsihao Yang, Yalin Wang
This paper studies 3D dense shape correspondence, a key shape analysis application in computer vision and graphics.
no code implementations • 12 Oct 2022 • Wenhui Zhu, Peijie Qiu, Natasha Lepore, Oana M. Dumitrascu, Yalin Wang
Lesion appearance is a crucial clue for medical providers to distinguish referable diabetic retinopathy (rDR) from non-referable DR.
2 code implementations • 10 May 2022 • Yu Fu, Yanyan Huang, Yalin Wang, Shunjie Dong, Le Xue, Xunzhao Yin, Qianqian Yang, Yiyu Shi, Cheng Zhuo
In this paper, we propose an end-to-end neural network architecture, referred to as optimal transport based feature pyramid fusion (OTFPF) network, for the brain age estimation with T1 MRIs.
no code implementations • 6 May 2022 • Haoteng Tang, Xiyao Fu, Lei Guo, Yalin Wang, Scott Mackin, Olusola Ajilore, Alex Leow, Paul Thompson, Heng Huang, Liang Zhan
Since brain networks derived from functional and structural MRI describe the brain topology from different perspectives, exploring a representation that combines these cross-modality brain networks is non-trivial.
no code implementations • 30 Oct 2021 • Yonghui Fan, Yalin Wang
Furthermore, we incorporate the feature learning of neural networks with the feature aggregation of Bayesian models to investigate the feasibility of jointly learning on manifolds.
no code implementations • 20 Oct 2021 • Jianfeng Wu, Wenhui Zhu, Yi Su, Jie Gui, Natasha Lepore, Eric M. Reiman, Richard J. Caselli, Paul M. Thompson, Kewei Chen, Yalin Wang
We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI).
no code implementations • 15 Jun 2021 • Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
Here we propose a topological receptive field (tRF) model which imposes the topological condition when decoding retinotopic fMRI signals.
no code implementations • ICCV 2021 • Min Zhang, Yang Guo, Na lei, Zhou Zhao, Jianfeng Wu, Xiaoyin Xu, Yalin Wang, Xianfeng GU
Shape analysis has been playing an important role in early diagnosis and prognosis of neurodegenerative diseases such as Alzheimer's diseases (AD).
no code implementations • 26 Oct 2020 • Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J Caselli, Eric M Reiman, Yalin Wang
With hippocampal UMIs, the estimated minimum sample sizes needed to detect a 25$\%$ reduction in the mean annual change with 80$\%$ power and two-tailed $P=0. 05$ are 116, 279 and 387 for the longitudinal $A\beta+$ AD, $A\beta+$ mild cognitive impairment (MCI) and $A\beta+$ CU groups, respectively.
no code implementations • 24 Aug 2020 • Yalin Wang, Xihan Chen, Yunlong Cai, Lajos Hanzo
Both the power-dissipation and cost of massive multiple-input multiple-output (mMIMO) systems may be substantially reduced by using low-resolution analog-to-digital converters (LADCs) at the receivers.
no code implementations • 19 Jul 2020 • Wen Zhang, Liang Zhan, Paul Thompson, Yalin Wang
The higher-order network mappings from brain structural networks to functional networks are learned in the node domain.
no code implementations • 25 May 2020 • Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
Although we focus on retinotopic mapping, the proposed framework is general and can be applied to process other human sensory maps.
4 code implementations • 9 Feb 2020 • Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Arman Eshaghi, Tina Toni, Marcin Salaterski, Veronika Lunina, Manon Ansart, Stanley Durrleman, Pascal Lu, Samuel Iddi, Dan Li, Wesley K. Thompson, Michael C. Donohue, Aviv Nahon, Yarden Levy, Dan Halbersberg, Mariya Cohen, Huiling Liao, Tengfei Li, Kaixian Yu, Hongtu Zhu, Jose G. Tamez-Pena, Aya Ismail, Timothy Wood, Hector Corrada Bravo, Minh Nguyen, Nanbo Sun, Jiashi Feng, B. T. Thomas Yeo, Gang Chen, Ke Qi, Shiyang Chen, Deqiang Qiu, Ionut Buciuman, Alex Kelner, Raluca Pop, Denisa Rimocea, Mostafa M. Ghazi, Mads Nielsen, Sebastien Ourselin, Lauge Sorensen, Vikram Venkatraghavan, Keli Liu, Christina Rabe, Paul Manser, Steven M. Hill, James Howlett, Zhiyue Huang, Steven Kiddle, Sach Mukherjee, Anais Rouanet, Bernd Taschler, Brian D. M. Tom, Simon R. White, Noel Faux, Suman Sedai, Javier de Velasco Oriol, Edgar E. V. Clemente, Karol Estrada, Leon Aksman, Andre Altmann, Cynthia M. Stonnington, Yalin Wang, Jianfeng Wu, Vivek Devadas, Clementine Fourrier, Lars Lau Raket, Aristeidis Sotiras, Guray Erus, Jimit Doshi, Christos Davatzikos, Jacob Vogel, Andrew Doyle, Angela Tam, Alex Diaz-Papkovich, Emmanuel Jammeh, Igor Koval, Paul Moore, Terry J. Lyons, John Gallacher, Jussi Tohka, Robert Ciszek, Bruno Jedynak, Kruti Pandya, Murat Bilgel, William Engels, Joseph Cole, Polina Golland, Stefan Klein, Daniel C. Alexander
TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease.
no code implementations • 13 Sep 2019 • Wen Zhang, Yalin Wang
Our model is a two-stage deep network which contains a coarse parcellation network with a U-shape structure and a refinement network to fine-tune the coarse results.
no code implementations • 20 Mar 2019 • Jie Zhang, Junting Zhang, Shalini Ghosh, Dawei Li, Jingwen Zhu, Heming Zhang, Yalin Wang
Lifelong learning, the problem of continual learning where tasks arrive in sequence, has been lately attracting more attention in the computer vision community.
no code implementations • 6 Mar 2019 • Wen Zhang, Kai Shu, Huan Liu, Yalin Wang
In particular, we provide a principled approach to jointly capture local and global information in the user-user social graph and propose the framework {\m}, which jointly learning user representations for user identity linkage.
no code implementations • 3 Feb 2019 • Jie Zhang, Xiaolong Wang, Dawei Li, Shalini Ghosh, Abhishek Kolagunda, Yalin Wang
State-of-the-art deep model compression methods exploit the low-rank approximation and sparsity pruning to remove redundant parameters from a learned hidden layer.
1 code implementation • 2 Dec 2018 • Liang Mi, Wen Zhang, Yalin Wang
We propose to align distributional data from the perspective of Wasserstein means.
2 code implementations • ECCV 2018 • Liang Mi, Wen Zhang, Xianfeng GU, Yalin Wang
We propose a new clustering method based on optimal transportation.
no code implementations • 4 Jun 2018 • Jie Zhang, Xiaolong Wang, Dawei Li, Yalin Wang
Recurrent neural networks (RNNs) achieve cutting-edge performance on a variety of problems.
no code implementations • ICCV 2017 • Liang Mi, Wen Zhang, Junwei Zhang, Yonghui Fan, Dhruman Goradia, Kewei Chen, Eric M. Reiman, Xianfeng GU, Yalin Wang
We compute the OT from each image to a template and measure the Wasserstein distance between them.
no code implementations • ICCV 2017 • Xiaokang Yu, Na lei, Yalin Wang, Xianfeng GU
In this paper, we propose a novel automatic method for non-rigid 3D dynamic surface tracking with surface Ricci flow and Teichmuller map methods.
no code implementations • 31 Aug 2017 • Jie Zhang, Qingyang Li, Richard J. Caselli, Jieping Ye, Yalin Wang
Firstly, we pre-train CNN on the ImageNet dataset and transfer the knowledge from the pre-trained model to the medical imaging progression representation, generating the features for different tasks.
no code implementations • 27 Apr 2017 • Qingyang Li, Dajiang Zhu, Jie Zhang, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang
Then we select the relevant group features by performing the group Lasso feature selection process in a sequence of parameters.
no code implementations • 19 Aug 2016 • Qingyang Li, Tao Yang, Liang Zhan, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang
To the best of our knowledge, this is the first successful run of the computationally intensive model selection procedure to learn a consistent model across different institutions without compromising their privacy while ranking the SNPs that may collectively affect AD.
no code implementations • CVPR 2016 • Jie Shi, Wen Zhang, Yalin Wang
Experimental results demonstrate that our method may be used as an effective shape index, which outperforms some other standard shape measures in our AD versus healthy control classification study.
no code implementations • CVPR 2013 • Rui Shi, Wei Zeng, Zhengyu Su, Hanna Damasio, Zhonglin Lu, Yalin Wang, Shing-Tung Yau, Xianfeng GU
This work conquer this problem by changing the Riemannian metric on the target surface to a hyperbolic metric, so that the harmonic mapping is guaranteed to be a diffeomorphism under landmark constraints.
no code implementations • CVPR 2013 • Zhengyu Su, Wei Zeng, Rui Shi, Yalin Wang, Jian Sun, Xianfeng GU
Experimental results on caudate nucleus surface mapping and cortical surface mapping demonstrate the efficacy and efficiency of the proposed method.