Enhanced Low-dose Computed Tomography – VISION AND IMAGE PROCESSING (VIP) RESEARCH GROUP

Andrew Cameron

Andrew Cameron — Thu, 23 Mar 2023 19:31:09 +0000

After being introduced to pattern recognition by Professor Paul Fieguth during my undergraduate degree, I sought to learn more about pattern classification and machine learning by applying them to a variety of academic and work term projects including touch input recognition and EMG-based gesture recognition. Having completed my bachelor’s degree in Systems Design Engineering from the University of Waterloo, I am now pursuing a master’s degree under the supervision of Professor Alex Wong.

When I’m not writing papers or analyzing medical images, I enjoy digital and film photography.

Email: a4camero@uwaterloo.ca

Supervisors

Alexander Wong

Research interests

I’m interested in automating and supporting complex reasoning tasks, including through applications of pattern classification, statistical modelling, image processing and computer vision, but also through data visualization, dimensionality reduction, and related techniques.

Research topics

Biomedical Imaging
Computer Vision
Image Segmentation/Classification
Stochastic Models

Research demos

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

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Dorothy Lui

Dorothy Lui — Thu, 23 Mar 2023 19:29:04 +0000

I completed my bachelor’s in Mechatronics Engineering at the University of Waterloo in 2012. I am now pursuing my master’s in Systems Design Engineering under the supervision of Prof. Wong. I was first exposed to image processing while working on in vivo bone implant images to determine bone porosity at the UW Rapid Prototyping Lab. Then, I worked at Colibri Technologies applying digital signal processing to ultrasound images.

Supervisors

Alexander Wong

Research interests

I am passionate about image processing and pattern recognition, particularly in applications in biomedical imaging. My current research involves developing new algorithms to automate segmentation of particular features in biomedical images.

Research topics

Biomedical Imaging
Computer Vision
Image Segmentation/Classification
Multiresolution Techniques
Stochastic Models

Research demos

Bias Field Correction in Endorectal Diffusion Imaging
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Enhanced Low-dose Computed Tomography
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation

Publications

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Daniel S. Cho

Daniel Cho — Thu, 23 Mar 2023 17:36:21 +0000

I received a bachelor’s degree in biomedical computing at the Queen’s University, and a M.E.Sc degree in biomedical engineering at the University of Western Ontario. I am a current PhD student at the University of Waterloo.

Supervisors

Alexander Wong, David Clausi

Research interests

My research interests are in image processing, medical image registration and reconstruction and I am currently working on computer-aided melanoma (one type of skin cancer) diagnosis through the modeling of physiological characteristics of skin lesions using multi-spectral imagery.

Research topics

Biomedical Imaging
Computer Vision
Image Segmentation/Classification

Research demos

Enhanced Low-dose Computed Tomography
Skin Cancer Detection

Publications

Journal Articles / Conference Papers

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Conference Papers

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Enhanced Low-dose Computed Tomography

vipadmin — Tue, 21 Mar 2023 15:59:45 +0000

Computed tomography (CT) is a useful imaging modality for visualizing organs, bones and tissue as cross-sectional images using X-ray. The X-rays however, introduce the body to radiation which over time in high doses can lead to cancer. Low-dose CT is a more desirable alternative however it has reduced signal-to-noise ratio (SNR) and streaking artifacts that make diagnosis and visualization difficult. Noise in low-dose CT can be caused by a number of reasons such as quantum noise and sensor and hardware equipment phenomena. Moreover the noise in reconstructed CT images result in unknown noise distributions with spatially changing noise statistics.

Existing approaches correct for the noise prior to, during or following reconstruction. This work proposes a reconstruction approach called Spatially Adaptive Monte Carlo Reconstruction (SAMCR) that corrects for the non-stationary noise in low-dose CT using a spatially-adaptive approach. The noise-compensated reconstruction is estimated using non-parametric modeling based on a spatially-adaptive Monte Carlo sampling approach. The resulting reconstructions effectively compensate for varying levels of noise, streaking artifacts and detail without introducing new artifacts or removing fine structures. The approach was investigated using phantoms and low-dose CT lung images. See Fig. for examples.

Fig. 1. An example low-dose CT slice with higher noise contamination. SAMCR effectively suppresses the noise and streaking artifacts while maintaining the fine details and structures within the lungs.

Fig. 2. An example low-dose CT slice with lower noise contamination. SAMCR preserves the details while accommodating for streaking noise without the introduction of artifacts.

Related people

Directors

Students

Alumni

Related research areas

Biomedical Imaging

Related publications

Journal Articles

Conference Papers

Alexander Wong

Alexander Wong — Thu, 23 Feb 2023 21:38:59 +0000

Alexander Wong is currently the Canada Research Chair in Medical Imaging Systems and an assistant professor in the Department of Systems Design Engineering at the University of Waterloo. He had previously received his B.A.Sc. degree in Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2005, his M.A.Sc. degree in Electrical and Computer Engineering from the University of Waterloo, Waterloo, ON, Canada in 2007, and his Ph.D. degree Systems Design Engineering from the University of Waterloo, ON, Canada in 2010. He was also a NSERC postdoctoral research fellow at Sunnybrook Health Sciences Centre. He has published over 450 refereed journal and conference papers, as well as patents, in various fields such as computational imaging, artificial intelligence, computer vision, and multimedia systems. He has received numerous awards including three Outstanding Performance Awards, a Distinguished Performance Award, an Engineering Research Excellence Award, a Sandford Fleming Teaching Excellence Award, an Early Researcher Award from the Ministry of Economic Development and Innovation, a Best Paper Award at the NIPS Workshop on NIPS Workshop on Transparent and Interpretable Machine Learning (2017), a Best Paper Award at the NIPS Workshop on Efficient Methods for Deep Neural Networks (2016), two Best Paper Awards by the Canadian Image Processing and Pattern Recognition Society (CIPPRS) (2009 and 2014), a Distinguished Paper Award by the Society of Information Display (2015), two Best Paper Awards for the Conference of Computer Vision and Imaging Systems (CVIS) (2015,2017), Synaptive Best Medical Imaging Paper Award (2016), two Magna Cum Laude Awards and one Cum Laude Award from the Annual Meeting of the Imaging Network of Ontario, CIX TOP 20 (2017), AquaHacking Challenge First Prize (2017), Best Student Paper at Ottawa Hockey Analytics Conference (2017), and the Alumni Gold Medal.

Students

Supervision – Current

PDF

ph.D.

M.A.Sc.

Supervision – Completed

PDF

ph.D.

M.A.Sc.

Research topics

Biomedical Imaging
Computer Vision
Discovery Radiomics
Evolutionary Deep Intelligence
Image Segmentation/Classification
Multiresolution Techniques
Remote Sensing
Scientific Imaging
Stochastic Models
Video Analysis

Research demos

Action Recognition in Video
Bias Field Correction in Endorectal Diffusion Imaging
Coded Hemodynamic Imaging
Correlated Diffusion Imaging
Disparate Scene Registration
Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Enhanced Low-dose Computed Tomography
Grid Seams: A fast superpixel algorithm for real-time applications
Hybrid Structural and Texture Distinctiveness Vector Field Convolution for Region Segmentation
Image Denoising
Multiplexed Optical High-coherence Interferometry
SAR Sea Ice Image Synthesis
Skin Cancer Detection
Statistical Textural Distinctiveness for Salient Region Detection in Natural Images
Stereo Vision for Dimension Estimation

Publications

Journal Articles / Conference Papers

Journal Articles

Conference Papers

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