Computational Interaction and Robotics Lab (CIRL) - Research

Surgical Modeling

We are interested in modeling and understanding the underlying structures in surgical motions. We would like to eventually use this understanding to create benchmarks for surgical skill evaluation, to develop methods for better surgical training and to automate the documentation of surgeries for libraries.

Human Machine Collaborative Systems

We are developing techniques for designing systems that amplify or assist human physical capabilities when performing tasks that require learned skills, judgement and dexterity. We refer to these systems as Human-machine Collaborative Systems (HMCS), as
they generally seek to combine human judgement and experience with physical and sensory augmentation using advanced display and robotic devices.

Image Segmentation

We have proposed a subspace labeling technique for global Image segmentation in a particular feature subspace is a fairly well understood problem.

XVision Real-Time Tracking System

XVision provides an application independent set of tools for visual feature tracking optimized to be simple to configure at the user level, yet extremely fast to execute.


RESEARCH
	Surgical Modeling We are interested in modeling and understanding the underlying structures in surgical motions. We would like to eventually use this understanding to create benchmarks for surgical skill evaluation, to develop methods for better surgical training and to automate the documentation of surgeries for libraries.

	Human Machine Collaborative Systems We are developing techniques for designing systems that amplify or assist human physical capabilities when performing tasks that require learned skills, judgement and dexterity. We refer to these systems as Human-machine Collaborative Systems (HMCS), as they generally seek to combine human judgement and experience with physical and sensory augmentation using advanced display and robotic devices.

	Motion Compensation in Cardiovascular MR Imaging Robust MR imaging of the coronary arteries is challenging due to the complex motion of these arteries induced by both respiratory and cardiac motion. Current approaches have had limited success due to the motion artifacts introduced by the variability in cardiac and respiratory motion during data acquisition. The effects of motion variability can be significantly reduced if the motion of the coronary artery can be estimated and used to guide MR image acquisition. We thus propose a method that involves acquiring high speed low-resolution images in specific orientations, extracting coronary motion to guide the high-resolution MR image acquisition. In order to show the feasibility of the proposed approach, we present and validate a multiple template tracking approach that allows reliable and accurate tracking of the left coronary artery (LCA) in low-resolution realtime MR image sequences in different orientations. We have also demonstrated using MR simulations that accounting for cardiac variability improves overall image quality.

	Real-time Video Mosaicking with Adaptive Parametrized Warping Image registration or alignment for video mosaicing has many research and real applications. Our motivations come primarily from the medical field, and primarily seek to over come fundamental field of view and resolution tradeoffs that occur ubiquitously in endoscopic surgery. There are two general approaches to computing the visual motions between successive images, the critical issue for registration. Direct approaches use all the image pixels available to compute an image-based error, which is then optimized. Complementary approaches are to specifically detect certain image features first then to estimate the corresponding relations between image feature pairs in different camera views. The latter often has the advantage of a larger range of convergence, although at the cost of a prior feature-detection and correspondence stage.

	Context-Aware Surgical Assistance for Virtual Mentoring Minimally invasive surgery (MIS) is a technique whereby instruments are inserted into the body via small incisions (or in some cases natural orifices), and surgery is carried out under video guidance. While presenting great advantages for the patient, MIS presents numerous challenges for the surgeon due to the restricted field of view presented by the endoscope, the tool motion constraints imposed by the insertion point, and the loss of haptic feedback. One means of overcoming some of these limitations is to present the surgeon with a registered three-dimensional overlay of information tied to pre-operative or intraoperative volumetric data. This data can provide guidance and feedback on the location of subsurface structures not apparent in endoscopic video data. Our objective is to develop algorithms for highly capable context-aware surgical assistant (CASA) robotic systems that are able to maintain a dynamically updated model of the surgical field and ongoing surgical procedure for the purposes of assistance, evaluation, and mentoring.

	Multi-Modality Retinal Image Registration Optical coherance tomography is a non-invasive imaging modality analogous to ultrasound using light rays. Registration of pre-operative OCT images to more familiar and easily available intra-operative fundus images allows precise location of pathologies which might otherwise be invisible, allowing a wider array of interventions.

	Micro-Surgical Assistant Workstation The Micro-Surgical Assistant Workstation is a system which is designed to aid and augment the performance of micro-surgical tasks by a human surgeon. A micro-surgical task is simply a surgical task which is performed on such a small scale that it must be done while looking through a microscope. The goals of the project include both the augmentation of physical skill at micro-manipulation and information fusion for better situational awareness during surgery.

	Computer Vision for Sinus Surgery

	Vision-Based Human Computer Interaction The Visual Interaction Cues (VICs) project is focused on developing new techniques for vision-based human computer interaction (HCI). The VICs paradigm is a methodology for vision-based interaction operating on the fundamental premise that, in general vision-based HCI settings, global user modeling and tracking are not necessary.

	Image Segmentation We have proposed a subspace labeling technique for global Image segmentation in a particular feature subspace is a fairly well understood problem.

	XVision Real-Time Tracking System XVision provides an application independent set of tools for visual feature tracking optimized to be simple to configure at the user level, yet extremely fast to execute.

	Mobile Robotics

	Robocup

	Functional Robotics


Advisor: Dr Gregory Hager	© Copyright	2005 - CIRL	Webmaster: Henry Lin