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GFA-Net: Global Feature Aggregation Network Based on Contrastive Learning for Breast Lesion Automated Segmentation in Ultrasound Images
Tao Wang;Chufeng Jin;Yang Chen;Guangquan Zhou;Rongjun Ge;Cheng Xue;Baike Shi;Tianyi Liu;Jean-Louis Coatrieux;Qianjin Feng
Accurate automatic segmentation of breast lesions in ultrasound images is a challenging auxiliary diagnostic task for automated deployment in breast cancer screening. In this study, a contrastive learning-based global feature aggregation network (GFA-Net) is proposed to reduce false detections and missed detections, thereby providing computer vision assistance for the development of automated equi...Show More
Minimum Variance Optimizations With Different Covariance Matrices in Plane-Wave Ultrasound Imaging
Su-Lan Pu;Hao Guo;Hui-Wen Xie;Chuan Chen;Ping Zhou;Guang-Quan Zhou
Coherent plane-wave compounding (CPWC) is a commonly applied beamforming technique for realizing ultrafast ultrasound imaging, though it often involves a trade-off in image quality. To address this limitation, the minimum variance distortionless response (MVDR) is advanced for the adaptive combination of ultrasound signals obtained from different directions. This process effectively suppresses the...Show More
TAGL: Temporal-Guided Adaptive Graph Learning Network for Coordinated Movement Classification
Le Li;Mingxia Zhang;Yuzhao Chen;Kaini Wang;Guangquan Zhou;Qinghua Huang
Deciphering coordinated movements is integral to understanding the daily activities and interactions between the nervous system and muscles, especially in robot-assisted rehabilitation. This study proposes a novel temporal-guided adaptive graph learning (TAGL) network to recognize coordinated movements from functional near-infrared spectroscopy (fNIRS) data. The temporal-guided node construction m...Show More
A Complementary Global and Local Knowledge Network for Ultrasound Denoising with Fine-grained Refinement
2024 7th International Symposium on Autonomous Systems (ISAS)
Year: 2024 | Conference Paper |
Ultrasound imaging serves as an effective and noninvasive diagnostic tool commonly employed in clinical examinations. However, the presence of speckle noise invariably degrades image quality, impeding the performance of subsequent tasks, such as classification and segmentation. Existing methods for speckle noise reduction frequently induce excessive image smoothing or fail to preserve detailed inf...Show More
PointDKT: Dual-Key Transformer for Point Cloud
2024 7th International Symposium on Autonomous Systems (ISAS)
Year: 2024 | Conference Paper |
Benefiting from the development of transformer-based networks in natural language processing and computer vision, researches on 3D point cloud understanding have made great progress in recent years. However, existing works often focus solely on aggregating local features or construct global dependencies through methods that significantly increase memory and computation complexity. Addressing these...Show More
Wavenumber Beamforming With Sub-Nyquist Sampling for Focus-Beam Ultrasound Imaging
Conventional medical ultrasound systems utilizing focus-beam imaging generally acquire multichannel echoes at frequencies in tens of megahertz after each transmission, resulting in significant data volumes for digital beamforming. Furthermore, integrating state-of-the-art beamformers with transmission compounding substantially increases the beamforming complexity. Except for upgrading the hardware...Show More
SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation
Kai-Ni Wang;Sheng-Xiao Li;Zhenyu Bu;Fu-Xing Zhao;Guang-Quan Zhou;Shou-Jun Zhou;Yang Chen
Automated segmentation of liver tumors in CT scans is pivotal for diagnosing and treating liver cancer, offering a valuable alternative to labor-intensive manual processes and ensuring the provision of accurate and reliable clinical assessment. However, the inherent variability of liver tumors, coupled with the challenges posed by blurred boundaries in imaging characteristics, presents a substanti...Show More
SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation
Juzheng Miao;Si-Ping Zhou;Guang-Quan Zhou;Kai-Ni Wang;Meng Yang;Shoujun Zhou;Yang Chen
Image segmentation achieves significant improvements with deep neural networks at the premise of a large scale of labeled training data, which is laborious to assure in medical image tasks. Recently, semi-supervised learning (SSL) has shown great potential in medical image segmentation. However, the influence of the learning target quality for unlabeled data is usually neglected in these SSL metho...Show More
Adaptive Frequency Learning Network With Anti-Aliasing Complex Convolutions for Colon Diseases Subtypes
Kaini Wang;Shuaishuai Zhuang;Juzheng Miao;Yang Chen;Jie Hua;Guang-Quan Zhou;Xiaopu He;Shuo Li
The automatic and dependable identification of colonic disease subtypes by colonoscopy is crucial. Once successful, it will facilitate clinically more in-depth disease staging analysis and the formulation of more tailored treatment plans. However, inter-class confusion and brightness imbalance are major obstacles to colon disease subtyping. Notably, the Fourier-based image spectrum, with its disti...Show More
DSANet: Dual-Branch Shape-Aware Network for Echocardiography Segmentation in Apical Views
Guang-Quan Zhou;Wen-Bo Zhang;Zhong-Qing Shi;Zhan-Ru Qi;Kai-Ni Wang;Hong Song;Jing Yao;Yang Chen
Echocardiography is an essential examination for cardiac disease diagnosis, from which anatomical structures segmentation is the key to assessing various cardiac functions. However, the obscure boundaries and large shape deformations due to cardiac motion make it challenging to accurately identify the anatomical structures in echocardiography, especially for automatic segmentation. In this study, ...Show More
Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements
Guang-Quan Zhou;Shi-Hao Hua;Yikang He;Kai-Ni Wang;Dandan Zhou;Hongxing Wang;Ruoli Wang
Tracking the myotendinous junction (MTJ) motion in consecutive ultrasound images is essential to assess muscle and tendon interaction and understand the mechanics’ muscle-tendon unit and its pathological conditions during motion. However, the inherent speckle noises and ambiguous boundaries deter the reliable identification of MTJ, thus restricting their usage in human motion analysis. This study ...Show More
Robust Super-Resolution Ultrasound Microbubble Tracking with Optical Flow Guided Kalman Filter
2022 IEEE International Ultrasonics Symposium (IUS)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
This paper describes a contribution to the Ultrasound Localization and TRacking Algorithms for Super Resolution (ULTRA-SR) Challenge. As a potential strategy for clinical applications, super-resolution (SR) imaging overcomes the diffraction limit and achieves sub-wavelength spatial resolution imaging by locating microbubble (MB) contrast agents and stacking them in multiple frames. To obtain SR im...Show More
A Study of Bandwidth Extension in Delay Multiply and Sum Beamforming applied to Ultrasound Imaging
Hui-Wen Xie;Hao Guo;Guang-Quan Zhou;Nghia Q. Nguyen;Richard W. Prager
2022 IEEE International Ultrasonics Symposium (IUS)
Year: 2022 | Conference Paper |
We have combined Filtered Delay Multiply and Sum (F-DMAS) beamforming with our previous unified Pixel-based (unified PB) framework to simultaneously improve ultrasound imaging resolution and contrast. However, the F-DMAS requires the oversampling of RF data to avoid aliasing, increasing the complexity and volume of data acquisition and the computational load. This oversampling requirement also com...Show More
Fourier-Domain Beamforming and Sub-Nyquist Sampling for Coherent Pixel-Based Ultrasound Imaging
2022 IEEE International Ultrasonics Symposium (IUS)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
Coherent pixel-based beamforming has been developed for generating uniform high-resolution ultrasound images. It is based on the conventional architecture of ultrasonic systems using fixed-focused beams to acquire data. The image generation, however, is time-consuming as it requires data superposition from a large number of transmits. In this study, we integrate a frequency-domain beamforming fram...Show More
Online Hard Patch Mining Using Shape Models and Bandit Algorithm for Multi-Organ Segmentation
Hard sample selection can effectively improve model convergence by extracting the most representative samples from a training set. However, due to the large capacity of medical images, existing sampling strategies suffer from insufficient exploitation for hard samples or high time cost for sample selection when adopted by 3D patch-based models in the field of multi-organ segmentation. In this pape...Show More
A combination of pixel-based beamforming and Wiener filter to improve ultrasound image quality
Hui-Wen Xie;Hao Guo;Guang-Quan Zhou;Nghia Q. Nguyen;Richard W. Prager
2021 IEEE International Ultrasonics Symposium (IUS)
Year: 2021 | Conference Paper |
We previously developed coherent pixel-based beamforming to generate two-way focused ultrasound images, where the transmit focusing is achieved by accumulating data from multiple transmits. Most of the impact of this, however, is on the lateral resolution which directly benefits from the large “effective” aperture. In this study we extend the field pattern analysis and form a new Wiener filter tha...Show More
High-resolution ultrasound imaging using unified pixel-based and filtered delay multiply and sum beamforming
Hao Guo;Hui-Wen Xie;Guang-Quan Zhou;Nghia Q. Nguyen;Richard W. Prager
2021 IEEE International Ultrasonics Symposium (IUS)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Unified pixel-based (PB) beamforming has previously been implemented for ultrasound imaging. It was shown to offer significant enhancements in lateral resolution compared to conventional dynamic focusing. Yet, there is still interference from clutter and high sidelobe artefacts that limit the the contrast resolution. In this paper, we propose a combination of the unified pixel-based approach with ...Show More
Generalize Ultrasound Image Segmentation Via Instant And Plug & Play Style Transfer
Zhendong Liu;Xiaoqiong Huang;Xin Yang;Rui Gao;Rui Li;Yuanji Zhang;Yankai Huang;Guangquan Zhou;Yi Xiong;Alejandro F Frangi;Dong Ni
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis. Retraining models leads to high latency and complex pipelines, which are impractical in clinical settings. The situation becomes more severe for ultrasound image analysis because of their large appearance shifts. In this paper, we propose a novel method for robust segment...Show More
Learn Fine-Grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images
Guang-Quan Zhou;Juzheng Miao;Xin Yang;Rui Li;En-Ze Huo;Wenlong Shi;Yuhao Huang;Jikuan Qian;Chaoyu Chen;Dong Ni
Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent deep learning methods have improved results by directly encoding the appearance of the captured anatomy with the likelihood maps (i.e., heatmaps). However, most current solutions overlook another essence of heatmap regression, the objective metric fo...Show More
Para-sagittal Midclavicular Plane Localization in 3DCT Using Multi-Agent Dueling Network
2020 5th International Conference on Communication, Image and Signal Processing (CCISP)
Year: 2020 | Conference Paper |
Locating the para-sagittal on the left portal vein in the abdominal enhanced 3DCT data is a critical step in clinical diagnosis and multi-modality fusion. The process of manually annotating landmarks on the anatomical structure is timeconsuming, laborious, and requires a wealth of professional knowledge. In recent years, reinforcement learning (RL) has developed rapidly, making it possible to deal...Show More
Ultrasound Sagittal Projection Imaging for the Assessment of Scoliosis
Dong-Sheng Li;Guang-Quan Zhou;Yi-Kang He;Ping Zhou;Si-Yuan He;Yong-Ping Zheng
2020 IEEE International Ultrasonics Symposium (IUS)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
The scoliosis assessment on both the coronal and sagittal planes is as least as necessary. However, it has a healthy risk to take X-ray examinations for obtaining both radiographs, especially to teenagers. 3-D ultrasound imaging shows the potential for radiation-free scoliosis assessment. In this paper, we develop a novel projection imaging method to obtain the sagittal visualization of spine anat...Show More
A Single-Shot Region-Adaptive Network for Myotendinous Junction Segmentation in Muscular Ultrasound Images
Guang-Quan Zhou;En-Ze Huo;Mei Yuan;Ping Zhou;Ruo-Li Wang;Kai-Ni Wang;Yang Chen;Xiao-Pu He
Tracking the myotendinous junction (MTJ) in consecutive ultrasound images is crucial for understanding the mechanics and pathological conditions of the muscle-tendon unit. However, the lack of reliable and efficient identification of MTJ due to poor image quality and boundary ambiguity restricts its application in motion analysis. In recent years, with the rapid development of deep learning, the r...Show More
Automatic Measurement of Spine Curvature on 3-D Ultrasound Volume Projection Image With Phase Features
This paper presents an automated measurement of spine curvature by using prior knowledge on vertebral anatomical structures in ultrasound volume projection imaging (VPI). This method can be used in scoliosis assessment with free-hand 3-D ultrasound imaging. It is based on the extraction of bony features from VPI images using a newly proposed two-fold thresholding strategy, with information of the ...Show More
Assessment of scoliosis using 3-D ultrasound volume projection imaging with automatic spine curvature detection
2015 IEEE International Ultrasonics Symposium (IUS)
Year: 2015 | Conference Paper |
Cited by: Papers (8)
X-ray imaging is a gold standard to diagnose scoliosis, a medical condition defined as lateral spine curvature > 10°. However, radiation hazard restricts its application. 3-D ultrasound imaging shows potential for radiation-free scoliosis assessment. Recently, ultrasound volume projection imaging (VPI) was reported to provide a coronal view of spine for manual measurement of spine curvature. An au...Show More
Automatic Fascicle Length Estimation on Muscle Ultrasound Images With an Orientation-Sensitive Segmentation
Goal: The fascicle length obtained by ultrasound imaging is one of the crucial muscle architecture parameters for understanding the contraction mechanics and pathological conditions of muscles. However, the lack of a reliable automatic measurement method restricts the application of the fascicle length for the analysis of the muscle function, as frame-by-frame manual measurement is time-consuming....Show More
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