Search Results for author: Juan Liu

Found 14 papers, 0 papers with code

Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement

no code implementations28 Jul 2021 Juan Liu, Masoud Malekzadeh, Niloufar Mirian, Tzu-An Song, Chi Liu, Joyita Dutta

High noise and low spatial resolution are two key confounding factors that limit the qualitative and quantitative accuracy of PET images.

Deblurring Image Denoising +1

Improved Padding in CNNs for Quantitative Susceptibility Mapping

no code implementations21 Jun 2021 Juan Liu

Recently, deep learning methods have been proposed for quantitative susceptibility mapping (QSM) data processing: background field removal, field-to-source inversion, and single-step QSM reconstruction.

The dynamic energy balance in earthquakes expressed by fault surface morphology

no code implementations18 Jan 2021 Xin Wang, Juan Liu, Feng Gao, Zhizhen Zhang

The fault surface morphology is the direct result of the microscopic processes near the crack tip or on the frictional interface.


Weakly-supervised Learning for Single-step Quantitative Susceptibility Mapping

no code implementations14 Aug 2020 Juan Liu, Kevin M. Koch

wTFI uses the BFR method RESHARP local fields as supervision to perform a multi-task learning of local tissue fields and QSM, and is capable of recovering magnetic susceptibility estimates near the edges of the brain where are eroded in RESHARP and realize whole brain QSM estimation.

Multi-Task Learning

An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety

no code implementations30 Apr 2020 Jing Han, Kun Qian, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu, Huaiyuan Zheng, Wei Ji, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, Björn W. Schuller

In particular, by analysing speech recordings from these patients, we construct audio-only-based models to automatically categorise the health state of patients from four aspects, including the severity of illness, sleep quality, fatigue, and anxiety.

Sleep Quality

COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis

no code implementations24 Mar 2020 Björn W. Schuller, Dagmar M. Schuller, Kun Qian, Juan Liu, Huaiyuan Zheng, Xiao Li

We come to the conclusion that CA appears ready for implementation of (pre-)diagnosis and monitoring tools, and more generally provides rich and significant, yet so far untapped potential in the fight against COVID-19 spread.

Meta-QSM: An Image-Resolution-Arbitrary Network for QSM Reconstruction

no code implementations1 Aug 2019 Juan Liu, Kevin M. Koch

In this work, we proposed a novel method called Meta-QSM to firstly solve QSM reconstruction of arbitrary image resolution with a single model.

Medical Physics Image and Video Processing

MRI Tissue Magnetism Quantification through Total Field Inversion with Deep Neural Networks

no code implementations11 Apr 2019 Juan Liu, Kevin M. Koch

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to infer estimates of local tissue magnetism (magnetic susceptibility), which has been shown useful to provide novel image contrast and as biomarkers of abnormal tissue.

Non-locally Encoder-Decoder Convolutional Network for Whole Brain QSM Inversion

no code implementations11 Apr 2019 Juan Liu, Kevin M. Koch

Quantitative Susceptibility Mapping (QSM) reconstruction is a challenging inverse problem driven by ill conditioning of its field-to -susceptibility transformation.


Group-sparse SVD Models and Their Applications in Biological Data

no code implementations28 Jul 2018 Wenwen Min, Juan Liu, Shihua Zhang

We employ an alternating direction method of multipliers (ADMM) to solve the proximal operator.

Variable Selection

Sparse Weighted Canonical Correlation Analysis

no code implementations13 Oct 2017 Wenwen Min, Juan Liu, Shihua Zhang

Given two data matrices $X$ and $Y$, sparse canonical correlation analysis (SCCA) is to seek two sparse canonical vectors $u$ and $v$ to maximize the correlation between $Xu$ and $Yv$.

Network-regularized Sparse Logistic Regression Models for Clinical Risk Prediction and Biomarker Discovery

no code implementations21 Sep 2016 Wenwen Min, Juan Liu, Shihua Zhang

To address it, we introduce a novel network-regularized sparse LR model with a new penalty $\lambda \|\bm{w}\|_1 + \eta|\bm{w}|^T\bm{M}|\bm{w}|$ to consider the difference between the absolute values of the coefficients.

L0-norm Sparse Graph-regularized SVD for Biclustering

no code implementations19 Mar 2016 Wenwen Min, Juan Liu, Shihua Zhang

Motivated by the development of sparse coding and graph-regularized norm, we propose a novel sparse graph-regularized SVD as a powerful biclustering tool for analyzing high-dimensional data.

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