Papers
9
Total Citations
133
H-Index
7
About
Jian-Qing Zheng is a researcher working at the intersection of medical robotics, computer vision, and deep learning, with a particular focus on advancing surgical navigation and microrobotic systems. His work addresses critical challenges in minimally invasive surgery, including 3D path planning for Fenestrated Endovascular Aortic Repair (FEVAR), where he pioneered methods to reconstruct three-dimensional anatomical guidance from single 2D fluoroscopic images — a contribution that has garnered over 30 citations across related publications. Zheng has made significant strides in medical image segmentation through his development of the Atrous Convolutional Neural Network (ACNN), a full-resolution deep learning architecture designed to preserve spatial detail critical for surgical navigation. His 2020 work on data-driven pose and depth estimation for optical microrobots, citing 33 times, demonstrates his ability to bring sophisticated machine learning techniques to microscale biomedical applications. More recently, he has explored self-supervised depth estimation in laparoscopic imaging using 3D geometric consistency, reflecting a growing interest in label-efficient learning for clinical environments. With contributions also spanning robotic dental implant preparation, Zheng's research consistently bridges cutting-edge AI methodology with tangible surgical and biomedical impact.
Research Focus
Key Achievements
Top Papers
- 1
- 2ACNN: a Full Resolution DCNN for Medical Image Segmentation24 citations · 2020
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- 5IEEE Robotics and Automation Letters publication information11 citations · 2019
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- 7ACNN: a Full Resolution DCNN for Medical Image Segmentation8 citations · 2019
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