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Christopher Y. Nguan

dblp:22/8528 · DBLP profile ↗
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7ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 6Graphics, computer vision, multimedia, augmented reality and games · 2Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%
Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.212013
Asymmetric force feedback control framework for teleoperated robot-assisted surgery · ICRA 2013
Robotics › Motion planning and robot control › robot control › human-in-the-loop control
teleoperation control
0.212013
Asymmetric force feedback control framework for teleoperated robot-assisted surgery · ICRA 2013
Haptics and multimodal interaction
haptic feedback
0.212013
Asymmetric force feedback control framework for teleoperated robot-assisted surgery · ICRA 2013
Medical and health informatics › surgical robotics
robot-assisted surgery
0.012013
Asymmetric force feedback control framework for teleoperated robot-assisted surgery · ICRA 2013

Methods — techniques the papers use, named apart from their topics

variable-structure controller · 0.5asymmetric force feedback · 0.5PD control · 0.5
YearPublicationVenuePosition
2018 Fast elastic registration of soft tissues under large deformations
Igor Peterlík, Hadrien Courtecuisse, Robert Rohling, Purang Abolmaesumi, Christopher Y. Nguan, Stephane Cotin, Tim Salcudean
Medical Image Anal.5
2015 Pico Lantern: Surface reconstruction and augmented reality in laparoscopic surgery using a pick-up laser projector
Philip Edgcumbe, Philip Pratt, Guang-Zhong Yang, Christopher Y. Nguan, Robert Rohling
Medical Image Anal.4
2014 Pico Lantern: A Pick-up Projector for Augmented Reality in Laparoscopic Surgery
Philip Edgcumbe, Philip Pratt, Guang-Zhong Yang, Christopher Y. Nguan, Robert Rohling
MICCAI (1)4
2013 Asymmetric force feedback control framework for teleoperated robot-assisted surgery
abstract
Lack of haptic feedback in teleoperated robot-assisted surgery (RAS) is known to be detrimental in many surgical tasks. While performing a class of force sensitive tasks, surgeons commonly use both hands. Oftentimes, one hand is used to exert tension/compression forces, and the other to hold the suture knot or tissue. A novel control framework to accomplish haptic force feedback for two-handed tasks in teleoperated RAS is presented in this paper. The force applied on the surgical environment by the action hand is not transferred back to the same hand, but rather to the other hand. In two-handed tasks that involve an action and a reaction force, this provides an intuitive way of feeling the action. Because the loop in not closed from the slave back to the master of the same hand, it does not have a destabilizing effect. The technique can be easily implemented using a variable-structure controller that combines two PD controllers and a switch. It has been evaluated with an experimental setup consisting of four haptic devices with promising results.
Omid Mohareri, Tim Salcudean, Christopher Y. Nguan
ICRA3
2012 Registration of 3D Ultrasound Through an Air-Tissue Boundary
abstract
In this study we evaluated a new method for registering three-dimensional ultrasound (3DUS) data to external coordinate systems. First, 3DUS was registered to the stereo endoscope of a da Vinci Surgical System by placing a registration tool against an air-tissue boundary so that the 3DUS could image ultrasound fiducials while the stereo endoscope could image camera markers on the same tool. The common points were used to solve the registration between the 3DUS and camera coordinate systems. The target registration error (TRE) when imaging through a PVC tissue phantom ranged from 3.85 1.76 mm to 1.82 1.03 mm using one to four registration tool positions. TRE when imaging through an ex-vivo liver tissue sample ranged from 2.36 1.01 mm to 1.51 0.70 mm using one to four registration tool positions. Second, using a similar method, 3DUS was registered to the kinematic coordinate system of a da Vinci Surgical System by using the da Vinci surgical manipulators to identify common points on an air-tissue boundary. TRE when imaging through a PVC tissue phantom was 0.95 0.38 mm. This registration method is simpler and potentially more accurate than methods using commercial motion tracking systems. This method may be useful in the future in augmented reality systems for laparoscopic and robotic-assisted surgery.
Troy K. Adebar, Michael C. Yip, Tim Salcudean, Robert Rohling, Christopher Y. Nguan, Larry Goldenberg
IEEE Trans. Medical Imaging5
2012 Tissue Tracking and Registration for Image-Guided Surgery
abstract
Vision-based tracking of tissue is a key component to enable augmented reality during a surgical operation. Conven- tional tracking techniques in computer vision rely on identifying strong edge features or distinctive textures in a well-lit environ- ment; however endoscopic tissue images do not have strong edge features, are poorly lit and exhibit a high degree of specular reflection. Therefore, prior work in achieving densely populated 3D features for describing tissue surface profiles require complex image processing techniques and have been limited in providing stable, long-term tracking or real-time processing. In this paper, we present an integrated framework for ac- curately tracking tissue in surgical stereo-cameras at real-time speeds. We use a combination of the STAR feature detector and Binary Robust Independent Elementary Features to acquire salient features that can be persistently tracked at high frame rates. The features are then used to acquire a densely-populated map of the deformations of tissue surface in 3D. We evaluate the method against popular feature algorithms in in-vivo animal study video sequences, and we also apply the proposed method to human partial nephrectomy video sequences. We extend the salient feature framework to support region tracking in order to maintain the spatial correspondence of a tracked region of tissue or a medical image registration to the surrounding tissue. In-vitro tissue studies show registration accuracies of 1.3-3.3 mm using a rigid-body transformation method.
Michael C. Yip, David G. Lowe, Tim Salcudean, Robert Rohling, Christopher Y. Nguan
IEEE Trans. Medical Imaging5
2010 3D Ultrasound to Stereoscopic Camera Registration through an Air-Tissue Boundary
Michael C. Yip, Troy K. Adebar, Robert Rohling, Tim Salcudean, Christopher Y. Nguan
MICCAI (2)5