Search Results for author: Zhongliang Jiang

Found 12 papers, 9 papers with code

Invisible Needle Detection in Ultrasound: Leveraging Mechanism-Induced Vibration

no code implementations21 Mar 2024 Chenyang Li, Dianye Huang, Angelos Karlas, Nassir Navab, Zhongliang Jiang

In clinical applications that involve ultrasound-guided intervention, the visibility of the needle can be severely impeded due to steep insertion and strong distractors such as speckle noise and anatomical occlusion.

Robot-Assisted Deep Venous Thrombosis Ultrasound Examination using Virtual Fixture

1 code implementation4 Jan 2024 Dianye Huang, Chenguang Yang, Mingchuan Zhou, Angelos Karlas, Nassir Navab, Zhongliang Jiang

To ensure the biometric measurements obtained in different examinations are comparable, the 6D scanning path is determined in a coarse-to-fine manner using both an external RGBD camera and US images.

Position

DefCor-Net: Physics-Aware Ultrasound Deformation Correction

1 code implementation7 Aug 2023 Zhongliang Jiang, Yue Zhou, Dongliang Cao, Nassir Navab

The recovery of morphologically accurate anatomical images from deformed ones is challenging in ultrasound (US) image acquisition, but crucial to accurate and consistent diagnosis, particularly in the emerging field of computer-assisted diagnosis.

Anatomy

Thoracic Cartilage Ultrasound-CT Registration using Dense Skeleton Graph

1 code implementation7 Jul 2023 Zhongliang Jiang, Chenyang Li, Xuesong Li, Nassir Navab

To address this challenge, a graph-based non-rigid registration is proposed to enable transferring planned paths from the atlas to the current setup by explicitly considering subcutaneous bone surface features instead of the skin surface.

Template Matching

Motion Magnification in Robotic Sonography: Enabling Pulsation-Aware Artery Segmentation

1 code implementation7 Jul 2023 Dianye Huang, Yuan Bi, Nassir Navab, Zhongliang Jiang

To validate the proposed robotic US system for imaging arteries, experiments are carried out on volunteers' carotid and radial arteries.

Motion Magnification Segmentation

Intelligent Robotic Sonographer: Mutual Information-based Disentangled Reward Learning from Few Demonstrations

1 code implementation7 Jul 2023 Zhongliang Jiang, Yuan Bi, Mingchuan Zhou, Ying Hu, Michael Burke, Nassir Navab

The results demonstrated that the proposed advanced framework can robustly work on a variety of seen and unseen phantoms as well as in-vivo human carotid data.

Navigate

DopUS-Net: Quality-Aware Robotic Ultrasound Imaging based on Doppler Signal

1 code implementation15 May 2023 Zhongliang Jiang, Felix Duelmer, Nassir Navab

The experimental results demonstrate that the proposed approach with the re-identification process can significantly improve the accuracy and robustness of the segmentation results (dice score: from 0:54 to 0:86; intersection over union: from 0:47 to 0:78).

Image Segmentation Region Proposal +2

Skeleton Graph-based Ultrasound-CT Non-rigid Registration

no code implementations14 May 2023 Zhongliang Jiang, Xuesong Li, Chenyu Zhang, Yuan Bi, Walter Stechele, Nassir Navab

Autonomous ultrasound (US) scanning has attracted increased attention, and it has been seen as a potential solution to overcome the limitations of conventional US examinations, such as inter-operator variations.

MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization

3 code implementations22 Mar 2023 Yuan Bi, Zhongliang Jiang, Ricarda Clarenbach, Reza Ghotbi, Angelos Karlas, Nassir Navab

We validate the generalizability of the proposed domain-independent segmentation approach on several datasets with varying parameters and machines.

Anatomy Disentanglement +5

Towards Autonomous Atlas-based Ultrasound Acquisitions in Presence of Articulated Motion

1 code implementation10 Aug 2022 Zhongliang Jiang, Yuan Gao, Le Xie, Nassir Navab

Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e. g. difficulty in guaranteeing intra- and inter-operator repeatability.

VesNet-RL: Simulation-based Reinforcement Learning for Real-World US Probe Navigation

1 code implementation10 May 2022 Yuan Bi, Zhongliang Jiang, Yuan Gao, Thomas Wendler, Angelos Karlas, Nassir Navab

The results demonstrate that proposed approach can effectively and accurately navigate the probe towards the longitudinal view of vessels.

Navigate reinforcement-learning +1

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