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Projects -
Medical Imaging
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Written by Emily J.Pico
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Tuesday, 21 April 2009 11:26 |
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Lab students Yunfeng Sui and Beibei Zhou accompanied Dr. Andrew Willis to this years SPIE Conference on Medical Imaging. They presented their work entitled "Improving Inter-fragmentary Alignment for Virtual 3D Reconstruction of Highly Fragmented Bone Fractures"
at the conference. This work is sponsored by the NIH under an R21 grant and seeks to quantify the severity of traumatic, i.e., highly fragmented, bone fractures involving many bone fragments. Such fractures often pose difficult problems for orthopeadic surgeons and have a higher instance of PTOA (Post-Traumatic Osteo-Arthritis). Our paper presented algorithms that semi-automatically aligns virtual models of bone fragments extracted from CT (computerized tomography) data. At the moment, we are validating results using surrogate bone material which can be measured accurately using a laser scanner and appears similar to human bones in CT images. Details are available in our paper.
The picture shows the three of us at the conference. Left to right: Yunfeng Sui, Dr. Andrew Willis and Beibei Zhou. |
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Last Updated on Wednesday, 23 September 2009 18:50 |
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News & Notices -
General News
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Written by Andrew Willis
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Tuesday, 01 July 2008 16:55 |
Graduate Research Assistant Positions Available
Electrical and Computer Engineering Department
There are up to three graduate-level research positions available for students in the Electrical and Computer Engineering Department. Students will be working with Dr. Andrew Willis in the Electrical and Computer Engineering department in the general field of signal processing, pattern recognition, and computer vision.
Requirements
- Applicants must have an interest in 3D graphics, image processing, statistics, pattern recognition and computer vision and plan on taking courses within these areas to develop their knowledge.
- Applicants must have good working knowledge and previous programming experience in C++, Java, or C (you will be tested).
- Applicants must have aptitude in mathematics (linear algebra) and experience in advanced signal processing.
What you will be researching
Students will develop algorithms and software for automatic recognition of structures within huge datasets, which are either 3D medical images or 3D (x,y,z) scans of real-world archaeological buildings. The work will consist mostly of programming in Java and analyze developed algorithms accuracy, computational cost, and performance relative to current state-of-the-art.
3D Medical Image Processing
The project will involve working on 3D Computerized Tomography (CT) images of fractured leg bones (the tibia & ankle region). A major goal of the project is to develop algorithms that will detect the fractured bones within the image and solve for the best alignment of the bone fragments to reconstruct the damaged limb.
3D Computer Vision with Archaeological Applications
This project will involve working on 3D (x,y,z) images of archaeological ruins with the intent of reconstructing damaged, missing, or obscured portions of the image. Students may be asked to travel to Israel during summers to perform data collection at an ancient Crusader-era castle, Apollonia-Arsuf, in Herzilya, Israel.
How to apply
Applications should be emailed to Dr. Andrew Willis (
This e-mail address is being protected from spambots. You need JavaScript enabled to view it
). The title of your email should indicate which position you are applying for and must include a resume (CV).
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Last Updated on Thursday, 03 July 2008 19:39 |
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Projects -
Embedded Vision Systems
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Written by Andrew Willis
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Thursday, 26 June 2008 09:33 |
Stereoscopic 3D Reconstruction using Motorized Zoom Lenses
within an Embedded System
Pengcheng Liu, Andrew Willis, Yunfeng Sui
UNC - Charlotte, 9201 University City Blvd., Charlotte, NC 28223
ABSTRACT
Motivation
Stereoscopic reconstruction systems are found in a number of environments and have been under development for over 20 years. Ongoing changes in imaging technologies have driven continual theoretical development and technical variations on the stereoscopic reconstruction problem. This paper describes a novel stereoscopic 3D reconstruction system meant to act as an 3D sensing payload for a terrestrial robot.
Methods
Novel theoretical and technical aspects of the system are tied to two aspects of the system design that deviate from typical stereoscopic reconstruction systems: (1) incorporation of an 10x zoom lens (Rainbow-H10x8.5) and (2) implementation of the system on an embedded DSP/FPGA system.
Hardware: The system is implemented on a mixed DSP/FPGA system consisting of a Blackfin DSP (BF537-ezkit) and a Xilinx Spartan3 FPGA. The DSP is tasked with orchestrating data flow through the system and complex computational tasks. The FPGA acts as an interface between the DSP and the system devices which include the camera CMOS sensors and the servo motors which rotate (pan) each camera. The entire system runs on an embedded version of the Linux operating system called μClinux which has 64MB of available memory.
Software: Calibration of the camera pair is accomplished using a collection of stereo images that view a common chess board calibration pattern for a set of pre-defined zoom positions. Calibration settings for an arbitrary zoom setting is then obtained by interpolation of the camera parameters. Classical techniques are use to rectify images using the estimated calibration parameters. Dense stereo matching is performed on the stereo image pairs using a custom adaptation of a dynamic programming algorithm proposed by Filho & Aloimonos in 2006 which requires little memory and provides high performance compared to other techniques while sacrificing accuracy by limiting the number of paths considered in the disparity space. Subsequent 3D surface reconstruction is accomplished by classical triangulation of the matched points from the disparity map.
Results:
The paper includes descriptions of and results for our solutions to the following problems: (1) automatic com
putation of the focus and exposure settings for the lens and camera sensor, (2) calibration of the system for various zoom settings, (3) automatic control of the extrinsic parameters as a function of the zoom setting to ensure the camera pair has an overlapping field-of-view, (4) our adaptation of the dense matching algorithm and (5) stereo reconstruction results for several free form objects. Preliminary results for reconstructing a small figurine are provided in figure 1.
Figure 1. (a) shows an image of the embedded system. (b,c) show images of the figurine from the left (b) and right (c) cameras respectively. (d) is a preliminary 3D reconstruction of the figurine.
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Last Updated on Monday, 30 June 2008 15:02 |
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