Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Zhou, Haoyin"'
Autor:
Zhou, Haoying
Scientists have been working on making robots act like human beings for decades. Therefore, how to imitate human motion has became a popular academic topic in recent years. Nevertheless, there are infinite trajectories between two points in three-dim
Externí odkaz:
https://hdl.handle.net/2144/40948
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
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
Intraoperative observation of tissue internal structure is often difficult. Hence, real-time soft tissue deformation is essential for the localization of tumor and other internal structures. We propose a method to simulate the internal structural def
Externí odkaz:
http://arxiv.org/abs/1907.10707
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Most machine learning-based coronary artery segmentation methods represent the vascular lumen surface in an implicit way by the centerline and the associated lumen radii, which makes the subsequent modeling process to generate a whole piece of watert
Externí odkaz:
http://arxiv.org/abs/1606.03014
Recently, machine learning has been successfully applied to model-based left ventricle (LV) segmentation. The general framework involves two stages, which starts with LV localization and is followed by boundary delineation. Both are driven by supervi
Externí odkaz:
http://arxiv.org/abs/1507.07508