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Grid Seams: A fast superpixel algorithm for real-time applications
Grid Seams is a novel seam carving approach to superpixel generation that preserves image structure information while enforcing a global spatial constraint in the form of a grid structure cost. The seam based approach allows us to obtain superpixels faster than all existing methods while maintaining a high image representation accuracy. Furthermore, our approach allows…
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Enhanced Low-dose Computed Tomography
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. 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.
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Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals
Active contours are a popular approach for object segmentation that uses an energy minimizing spline to extract an objects boundary. Non-parametric approaches can be computationally complex while parametric approaches can be impacted by parameter sensitivity. A decoupled active contour (DAC) overcomes these problems by decoupling the external and internal energies and optimizing them separately. However…
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Disparate Scene Registration
A problem of great interest in the field of visual pattern recognition is image registration, where images of the same scene captured under different conditions are aligned with each other. Image registration is important to a wide range of applications, such as environment change analysis, superresolution, biomedical image analysis, and computer-assisted surgery. Much of recent…
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Decoupled Active Contours
The accurate detection of object boundaries via active contours is an ongoing research topic in computer vision. Most active contours converge towards some desired contour by minimizing a sum of internal (prior) and external (image measurement) energy terms. Such an approach is elegant, but suffers from a slow convergence rate and frequently mis-converges in the…
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Computer Vision for Autonomous Robots
Exploration is an important and active area of research in field robotics, as vehicles capable of autonomous exploration have the potential to significantly impact a wide range of applications such as search and rescue operations, environmental monitoring, and planetary exploration. Such autonomous exploration capabilities are desirable for Lunar and Martian missions as tele-operation becomes cumbersome…
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Compressed Sensing
New imaging technologies have allowed us to see things at a new level of clarity and detail, or even see things that we were previously unable to visualize. However, a significant challenge faced by many new imaging technologies that limits widespread use for particular applications is long acquisition times. For example, despite the advantages associated…
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Coded Hemodynamic Imaging
Coded Hemodynamic Imaging (CHI), is a process where an innovative, highly-compact pulsed lighting and detection apparatus captures light fluctuations over time and space on various parts of the body simultaneously using spatiotemporal-coded pulse sequences. These spatiotemporal light fluctuation measurements are then relayed to a digital signal processing unit from which blood-flow patterns can be computed.…
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Bias Field Correction in Endorectal Diffusion Imaging
Diffusion-weighted MRI (DWI) has been useful in prognosis due to its improved visualization of dense cancerous tissue due to restricted diffusion of water in these regions. An additional endorectal coil has been used to improve the signal-to-noise ratio (SNR) in the prostate gland region however introduces an undesirable bias field which shows increased intensity nearest…