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of 180
pro vyhledávání: '"Jayender, Jagadeesan"'
This work tackles practical issues which arise when using a tendon-driven robotic manipulator (TDRM) with a long, flexible, passive proximal section in medical applications. Tendon-driven devices are preferred in medicine for their improved outcomes
Externí odkaz:
http://arxiv.org/abs/2301.00337
Autor:
Zhou, Haoyin, Jayender, Jagadeesan
The ability to extend the field of view of laparoscopy images can help the surgeons to obtain a better understanding of the anatomical context. However, due to tissue deformation, complex camera motion and significant three-dimensional (3D) anatomica
Externí odkaz:
http://arxiv.org/abs/2103.07414
Deformable image registration (DIR) is essential for many image-guided therapies. Recently, deep learning approaches have gained substantial popularity and success in DIR. Most deep learning approaches use the so-called mono-stream "high-to-low, low-
Externí odkaz:
http://arxiv.org/abs/2009.07151
Autor:
Zhou, Haoyin, Jayender, Jagadeesan
Publikováno v:
IEEE transactions on medical imaging 39, no. 2 (2019): 400-412
We propose an approach to reconstruct dense three-dimensional (3D) model of tissue surface from stereo optical videos in real-time, the basic idea of which is to first extract 3D information from video frames by using stereo matching, and then to mos
Externí odkaz:
http://arxiv.org/abs/2007.12623
Autor:
Zhou, Haoyin, Jayender, Jagadeesan
Tissue deformation during the surgery may significantly decrease the accuracy of surgical navigation systems. In this paper, we propose an approach to estimate the deformation of tissue surface from stereo videos in real-time, which is capable of han
Externí odkaz:
http://arxiv.org/abs/2007.08576
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence 41, no. 12 (2018): 3022-3033
The ability to handle outliers is essential for performing the perspective-n-point (PnP) approach in practical applications, but conventional RANSAC+P3P or P4P methods have high time complexities. We propose a fast PnP solution named R1PPnP to handle
Externí odkaz:
http://arxiv.org/abs/2007.08577
Autor:
Zhou, Haoyin, Jayender, Jagadeesan
This paper studies the mismatch removal problem, which may serve as the subsequent step of feature matching. Non-rigid deformation makes it difficult to remove mismatches because no parametric transformation can be found. To solve this problem, we fi
Externí odkaz:
http://arxiv.org/abs/2007.08553
Autor:
Wang, Duo, Li, Ming, Ben-Shlomo, Nir, Corrales, C. Eduardo, Cheng, Yu, Zhang, Tao, Jayender, Jagadeesan
Deep learning based medical image segmentation models usually require large datasets with high-quality dense segmentations to train, which are very time-consuming and expensive to prepare. One way to tackle this challenge is by using the mixed-superv
Externí odkaz:
http://arxiv.org/abs/1907.10209
Akademický článek
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Autor:
Wang, Duo, Li, Ming, Ben-Shlomo, Nir, Corrales, C. Eduardo, Cheng, Yu, Zhang, Tao *, Jayender, Jagadeesan *
Publikováno v:
In Computerized Medical Imaging and Graphics April 2021 89
