A5012878245- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Sparse and Compressive Sensing Techniques
- Speech and Audio Processing
- Cardiac Imaging and Diagnostics
- Advanced Neuroimaging Techniques and Applications
- Advanced X-ray and CT Imaging
- Advanced Adaptive Filtering Techniques
- Radiomics and Machine Learning in Medical Imaging
- Image and Signal Denoising Methods
- Music and Audio Processing
- MRI in cancer diagnosis
- Photoacoustic and Ultrasonic Imaging
- Atomic and Subatomic Physics Research
- Medical Image Segmentation Techniques
- Speech Recognition and Synthesis
- Ultrasound Imaging and Elastography
- Structural Health Monitoring Techniques
- Cerebrovascular and Carotid Artery Diseases
- Advanced X-ray Imaging Techniques
- Lung Cancer Diagnosis and Treatment
- Renal cell carcinoma treatment
- Acoustic Wave Phenomena Research
- Radiation Dose and Imaging
- Microwave Imaging and Scattering Analysis
Hunan Normal University
2019-2025
Hunan Provincial People's Hospital
2019-2025
Zhejiang University of Science and Technology
2025
Neusoft (China)
2017-2024
Fuzhou University
2022
Austrian Academy of Sciences
2017-2019
Zhejiang University
2019
Philips (China)
2013-2017
Acoustics Research Institute
2017
Chinese University of Hong Kong
2010-2014
Sparsity has been widely exploited for exact reconstruction of a signal from small number random measurements. Recent advances have suggested that structured or group sparsity often leads to more powerful techniques in various compressed sensing (CS) studies. In this paper, we propose nonlocal low-rank regularization (NLR) approach toward exploiting and explore its application into CS both photographic MRI images. We also the use nonconvex log det ( X) as smooth surrogate function rank...
Abstract A novel technique called “ k ‐ t GRAPPA” is introduced for the acceleration of dynamic magnetic resonance imaging. Dynamic images have significant signal correlations in ‐space and time dimension. Hence, it feasible to acquire only a reduced amount data recover missing portion afterward. Generalized autocalibrating partially parallel acquisitions (GRAPPA), as an important imaging technique, linearly interpolates ‐space. In this work, shown that idea GRAPPA can also be applied space...
The aim of this work is to improve the accuracy, robustness andefficiency compressed sensing reconstruction technique inmagnetic resonance imaging. We propose a novel variational modelthat enforces sparsity underlying image in terms itsspatial finite differences and representation with respect adictionary. dictionary trained using prior information toimprove accuracy reconstruction. In meantime proposedmodel consistency acquireddata by maximum likelihood estimator reconstructionerror partial...
This paper presents two fast algorithms for total variation–based image reconstruction in a magnetic resonance imaging technique known as partially parallel (PPI), where the inversion matrix is large and ill-conditioned. These utilize variable splitting techniques to decouple original problem into more easily solved subproblems. The first method reduces an unconstrained minimization problem, which by alternating proximal algorithm. One phase of algorithm solves variation (TV) denoising...
Purpose Increasing acquisition efficiency is always a challenge in high-resolution diffusion tensor imaging (DTI), which has low signal-to-noise ratio and sensitive to reconstruction artifacts. In this study, parallel (PI) compressed sensing (CS) combined framework proposed, features motion error correction, PI calibration, sparsity model using inter-image correlation tailored for DTI. Theory Methods The proposed method, named anisotropic SPIRiT, consists of three steps: (i) motion-induced...
Whole-heart coronary magnetic resonance angiography (MRA) is a promising method for noninvasive, radiation-free detection and exclusion of obstructive artery disease; however, the required imaging time robustness technique are not yet satisfactory. We evaluated value whole-heart MRA at 3.0T using 32-channel cardiac coil, which reduces image-acquisition times hence allows to increase clinical throughput.A total 110 consecutive patients with suspected disease referred clinically indicated...
Pitch estimation from acoustic signals is a fundamental problem in many areas of speech research. For noise-corrupted speech, reliable pitch difficult. This paper presents study noisy based on robust temporal-spectral representation and sparse reconstruction. We propose to accumulate spectral peaks over consecutive time frames. Since harmonic structure changes much more slowly than noise spectrum, related harmonics would stand out the through accumulation. Experimental results show that...
Both acquisition and reconstruction speed are crucial for magnetic resonance (MR) imaging in clinical applications. In this paper, we present a fast algorithm SENSE partially parallel MR with arbitrary k-space trajectories. The proposed method is combination of variable splitting, the classical penalty technique optimal gradient method. Variable splitting reformulate model sparsity regularization as an unconstrained minimization problem, which can be solved by alternating two simple...
Purpose A typical clinical MR examination includes multiple scans to acquire images with different contrasts for complementary diagnostic information. The multicontrast scheme requires long scanning time. combination of partially parallel imaging and compressed sensing (CS‐PPI) has been used reconstruct accelerated scans. However, there are several unsolved problems in existing methods. target this work is improve CS‐PPI methods imaging, especially two‐dimensional imaging. Theory Methods If...
Tumor imaging tools with high specificity and sensitivity are needed to aid the boundary recognition in solid tumor diagnosis surgical resection.In this study, we developed a near infra-red (NIR) probe (P6) for vitro/in vivo on basis of dual strategy cancer cell targeting stimulus-dependent activation.The selective capacity towards cells P6 was thoroughly investigated, potential mechanisms endocytosis were preliminary explored.Methods: GSH-activated biotin labelled NIR designed, synthesized...
PURPOSE: This retrospective study is designed to develop a Radiomics-based strategy for preoperatively predicting lymph node (LN) status in the resectable pancreatic ductal adenocarcinoma (PDAC) patients. METHODS: Eighty-five patients with histopathological confirmed PDAC are included, of which 35 LN metastasis positive and 50 negative. Initially, 1,124 radiomics features computed from CT images each patient. After series feature selection, Radiomics logistic regression (LOG) model...
To explore the feasibility of a one-beat protocol and ultra-low tube voltage 60 kVp in coronary CT angiography (CCTA). This prospective study enrolled 107 patients (body mass index ≤ 26 kg/m2) undergoing CCTA examinations. Specifically, conventional group (n = 52) underwent 100 scanning with 45 ml iodine contrast agent 4 ml/s injection rate, low-dose 55) 28 2.5 rate. The value, signal-noise-ratio (SNR), contrast-noise-ratio (CNR) subjective image quality score two groups aorta (AO), right...
Abstract Partially parallel imaging (PPI) is a widely used technique in clinical applications. A limitation of this the strong noise and artifact reconstructed images when high reduction factors are used. This work aims to increase applicability PPI by improving its performance at factors. new concept, image support reduction, introduced. systematic filter‐design approach for proposed. shows more advantages with an important existing technique, GRAPPA. An improved GRAPPA method, high‐pass...
Encouraging and astonishing developments have recently been achieved in image-based diagnostic technology. Modern medical care imaging technology are becoming increasingly inseparable. However, the current diagnosis pattern of signal to image knowledge inevitably leads information distortion noise introduction procedure reconstruction (from image). Artificial intelligence (AI) technologies that can mine from vast amounts data offer opportunities disrupt established workflows. In this...
A partial Fourier acquisition scheme has been widely adopted for fast imaging. There are two problems associated with the existing techniques. First, majority of techniques demodulate phase information and cannot provide improved over zero-padding. Second, serious artifacts can be observed in reconstruction when changes rapidly because low-resolution estimate image space is prone to error. To tackle these problems, a novel robust method introduced reconstruction, using k-space convolution....
Abstract A method for motion correction in multicoil imaging applications, involving both data collection and reconstruction, is presented. The floating navigator method, which acquires a readout line off center the phase‐encoding direction, expanded to detect translation/rotation inconsistent motion. This done by comparing with reference k ‐space region surrounding line, using correlation measure. technique of generalized autocalibrating partially parallel acquisition further developed...
Abstract Objective. In the realm of utilizing artificial intelligence (AI) for medical image analysis, paradigm ‘signal-image-knowledge’ has remained unchanged. However, process ‘signal to image’ inevitably introduces information distortion, ultimately leading irrecoverable biases in ‘image knowledge’ process. Our goal is skip reconstruction and build a diagnostic model directly from raw data (signal). Approach . This study focuses on computed tomography (CT) its (sinogram) as research...
Purpose To improve the performance of non‐Cartesian partially parallel imaging (PPI) by exploiting artificial sparsity, generalized autocalibrating acquisitions (GRAPPA) operator for wider band lines (GROWL) is taken as a specific example explanation. Theory This work based on GRAPPA‐like PPI having an improved when to‐be‐reconstructed image sparse in domain. Methods A systematic scheme proposed to artificially generate trajectory. Using GROWL method, sparsity‐enhanced (ARTS‐GROWL) used...
Abstract Purpose To investigate the effectiveness of k‐t GRAPPA for accelerating four‐dimensional (4D) coronary MRA in comparison with and feasibility combining variable density undersampling conventional (k‐t 2 GRAPPA) to alleviate overhead acquiring autocalibration signals. Materials Methods The right artery nine healthy volunteers was scanned at 1.5 Tesla. 4D k ‐space datasets were fully acquired subsequently undersampled simulate partially parallel acquisitions, namely, GRAPPA, GRAPPA....