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- Article
Explainable and Controllable Motion Curve Guided Cardiac Ultrasound Video Generation
- Junxuan Yu,
- Rusi Chen,
- Yongsong Zhou,
- Yanlin Chen,
- Yaofei Duan,
- Yuhao Huang,
- Han Zhou,
- Tao Tan,
- Xin Yang,
- Dong Ni
Machine Learning in Medical Imaging•October 2024, pp 232-241• https://doi.org/10.1007/978-3-031-73290-4_23AbstractEchocardiography video is a primary modality for diagnosing heart diseases, but the limited data poses challenges for both clinical teaching and machine learning training. Recently, video generative models have emerged as a promising strategy to ...
- Article
Robust Box Prompt Based SAM for Medical Image Segmentation
Machine Learning in Medical Imaging•October 2024, pp 1-11• https://doi.org/10.1007/978-3-031-73290-4_1AbstractThe Segment Anything Model (SAM) can achieve satisfactory segmentation performance under high-quality box prompts. However, SAM’s robustness is compromised by the decline in box quality, limiting its practicality in clinical reality. In this study,...
- Article
Mitral Regurgitation Recogniton Based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification
- Zhe Liu,
- Xiliang Zhu,
- Tong Han,
- Yuhao Huang,
- Jian Wang,
- Lian Liu,
- Fang Wang,
- Dong Ni,
- Zhongshan Gou,
- Xin Yang
Machine Learning in Medical Imaging•October 2024, pp 52-62• https://doi.org/10.1007/978-3-031-73284-3_6AbstractMitral regurgitation (MR) is a serious heart valve disease. Early and accurate diagnosis of MR via ultrasound video is critical for timely clinical decision-making and surgical intervention. However, manual MR diagnosis heavily relies on the ...
- Article
EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image Segmentation
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024•October 2024, pp 266-275• https://doi.org/10.1007/978-3-031-72114-4_26AbstractConvolutional neural networks have primarily led 3D medical image segmentation but may be limited by small receptive fields. Transformer models excel in capturing global relationships through self-attention but are challenged by high computational ...
- research-article
Recurrent feature propagation and edge skip-connections for automatic abdominal organ segmentation
Expert Systems with Applications: An International Journal, Volume 249, Issue PC•Sep 2024 • https://doi.org/10.1016/j.eswa.2024.123856AbstractAutomatic segmentation of abdominal organs in computed tomography (CT) images can support radiation therapy and image-guided surgery workflows. Development of such automatic solutions remains challenging mainly owing to complex organ interactions ...
Highlights- Proposes an end-to-end 3D network for the challenging abdominal organ segmentation.
- Focuses on effective spatial context modeling and explicit edge segmentation priors.
- Incorporates wide-range contextual dependencies via directed ...
- research-article
An efficient framework for lesion segmentation in ultrasound images using global adversarial learning and region-invariant loss
Computers in Biology and Medicine, Volume 171, Issue C•Mar 2024 • https://doi.org/10.1016/j.compbiomed.2024.108137AbstractLesion segmentation in ultrasound images is an essential yet challenging step for early evaluation and diagnosis of cancers. In recent years, many automatic CNN-based methods have been proposed to assist this task. However, most modern approaches ...
Highlights- A segmentation framework that focuses on global information and invariant features.
- A global adversarial learning mechanism with a self-attention-based discriminator.
- Embedding lesion texture information into a region-invariant ...
- research-article
Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training
- Jian Wang,
- Xin Yang,
- Xiaohong Jia,
- Wufeng Xue,
- Rusi Chen,
- Yanlin Chen,
- Xiliang Zhu,
- Lian Liu,
- Yan Cao,
- Jianqiao Zhou,
- Dong Ni,
- Ning Gu
Computers in Biology and Medicine, Volume 171, Issue C•Mar 2024 • https://doi.org/10.1016/j.compbiomed.2024.108087AbstractThyroid nodule classification and segmentation in ultrasound images are crucial for computer-aided diagnosis; however, they face limitations owing to insufficient labeled data. In this study, we proposed a multi-view contrastive self-supervised ...
Highlights- We proposed a multi-view SSL method that is not constrained by paired views.
- We adopted a two-stage pre-training strategy on thyroid ultrasound images.
- Extensive experiments were conducted on a large thyroid ultrasound image ...
- research-article
Non-iterative scribble-supervised learning with pacing pseudo-masks for medical image segmentation▪
Expert Systems with Applications: An International Journal, Volume 238, Issue PC•Mar 2024 • https://doi.org/10.1016/j.eswa.2023.122024AbstractScribble-supervised medical image segmentation tackles the limitation of sparse masks. Conventional approaches alternate between: labeling pseudo-masks and optimizing network parameters. However, such iterative two-stage paradigm is unwieldy and ...
Highlights- A simple yet effective non-iterative method for scribble-supervised segmentation.
- Entropy regularization to obtain high-confidence pseudo-masks for effective teaching.
- Distorted augmentations to create discrepancy for consistency ...
- Article
PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation
Machine Learning in Medical Imaging•October 2023, pp 257-266• https://doi.org/10.1007/978-3-031-45673-2_26AbstractInteractive medical image segmentation refers to the accurate segmentation of the target of interest through interaction (e.g., click) between the user and the image. It has been widely studied in recent years as it is less dependent on abundant ...
- Article
FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation
Machine Learning in Medical Imaging•October 2023, pp 166-175• https://doi.org/10.1007/978-3-031-45673-2_17AbstractUltrasound (US) image segmentation is an active research area that requires real-time and highly accurate analysis in many scenarios. The detect-to-segment (DTS) frameworks have been recently proposed to balance accuracy and efficiency. However, ...
- Article
ModeT: Learning Deformable Image Registration via Motion Decomposition Transformer
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 740-749• https://doi.org/10.1007/978-3-031-43999-5_70AbstractThe Transformer structures have been widely used in computer vision and have recently made an impact in the area of medical image registration. However, the use of Transformer in most registration networks is straightforward. These networks often ...
- Article
GSMorph: Gradient Surgery for Cine-MRI Cardiac Deformable Registration
- Haoran Dou,
- Ning Bi,
- Luyi Han,
- Yuhao Huang,
- Ritse Mann,
- Xin Yang,
- Dong Ni,
- Nishant Ravikumar,
- Alejandro F. Frangi,
- Yunzhi Huang
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 613-622• https://doi.org/10.1007/978-3-031-43999-5_58AbstractDeep learning-based deformable registration methods have been widely investigated in diverse medical applications. Learning-based deformable registration relies on weighted objective functions trading off registration accuracy and smoothness of ...
- Article
Mitral Regurgitation Quantification from Multi-channel Ultrasound Images via Deep Learning
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 223-232• https://doi.org/10.1007/978-3-031-43987-2_22AbstractMitral regurgitation (MR) is the most common heart valve disease. Prolonged regurgitation can cause changes in the heart size, lead to impaired systolic and diastolic capacity, and even threaten life. In clinical practice, MR is evaluated by the ...
- Article
Wall Thickness Estimation from Short Axis Ultrasound Images via Temporal Compatible Deformation Learning
- Ang Zhang,
- Guijuan Peng,
- Jialan Zheng,
- Jun Cheng,
- Xiaohua Liu,
- Qian Liu,
- Yuanyuan Sheng,
- Yingqi Zheng,
- Yumei Yang,
- Jie Deng,
- Yingying Liu,
- Wufeng Xue,
- Dong Ni
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 213-222• https://doi.org/10.1007/978-3-031-43987-2_21AbstractStructural parameters of the heart, such as left ventricular wall thickness (LVWT), have important clinical significance for cardiac disease. In clinical practice, it requires tedious labor work to be obtained manually from ultrasound images and ...
- Article
Multi-IMU with Online Self-consistency for Freehand 3D Ultrasound Reconstruction
- Mingyuan Luo,
- Xin Yang,
- Zhongnuo Yan,
- Junyu Li,
- Yuanji Zhang,
- Jiongquan Chen,
- Xindi Hu,
- Jikuan Qian,
- Jun Cheng,
- Dong Ni
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 342-351• https://doi.org/10.1007/978-3-031-43907-0_33AbstractUltrasound (US) imaging is a popular tool in clinical diagnosis, offering safety, repeatability, and real-time capabilities. Freehand 3D US is a technique that provides a deeper understanding of scanned regions without increasing complexity. ...
- Article
MUVF-YOLOX: A Multi-modal Ultrasound Video Fusion Network for Renal Tumor Diagnosis
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 642-651• https://doi.org/10.1007/978-3-031-43904-9_62AbstractEarly diagnosis of renal cancer can greatly improve the survival rate of patients. Contrast-enhanced ultrasound (CEUS) is a cost-effective and non-invasive imaging technique and has become more and more frequently used for renal tumor diagnosis. ...
- Article
Instructive Feature Enhancement for Dichotomous Medical Image Segmentation
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 437-447• https://doi.org/10.1007/978-3-031-43901-8_42AbstractDeep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance. However, existing networks tend to struggle with task-specific, ...
- Article
Fourier Test-Time Adaptation with Multi-level Consistency for Robust Classification
- Yuhao Huang,
- Xin Yang,
- Xiaoqiong Huang,
- Xinrui Zhou,
- Haozhe Chi,
- Haoran Dou,
- Xindi Hu,
- Jian Wang,
- Xuedong Deng,
- Dong Ni
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 221-231• https://doi.org/10.1007/978-3-031-43898-1_22AbstractDeep classifiers may encounter significant performance degradation when processing unseen testing data from varying centers, vendors, and protocols. Ensuring the robustness of deep models against these domain shifts is crucial for their widespread ...
- Article
Inflated 3D Convolution-Transformer for Weakly-Supervised Carotid Stenosis Grading with Ultrasound Videos
- Xinrui Zhou,
- Yuhao Huang,
- Wufeng Xue,
- Xin Yang,
- Yuxin Zou,
- Qilong Ying,
- Yuanji Zhang,
- Jia Liu,
- Jie Ren,
- Dong Ni
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023•October 2023, pp 511-520• https://doi.org/10.1007/978-3-031-43895-0_48AbstractLocalization of the narrowest position of the vessel and corresponding vessel and remnant vessel delineation in carotid ultrasound (US) are essential for carotid stenosis grading (CSG) in clinical practice. However, the pipeline is time-consuming ...
- research-article
Test-time bi-directional adaptation between image and model for robust segmentation
- Xiaoqiong Huang,
- Xin Yang,
- Haoran Dou,
- Yuhao Huang,
- Li Zhang,
- Zhendong Liu,
- Zhongnuo Yan,
- Lian Liu,
- Yuxin Zou,
- Xindi Hu,
- Rui Gao,
- Yuanji Zhang,
- Yi Xiong,
- Wufeng Xue,
- Dong Ni
Computer Methods and Programs in Biomedicine, Volume 233, Issue C•May 2023 • https://doi.org/10.1016/j.cmpb.2023.107477Highlights- An effective test-time bi-directional adaptation strategy is proposed to seek robust segmentation.
- A window-based order statistics alignment module is presented to adapt appearance-agnostic test images to existing learned models.
- ...
Abstract Background and objectiveDeep learning models often suffer from performance degradations when deployed in real clinical environments due to appearance shifts between training and testing images. Most extant methods use training-time adaptation, ...