Jeff Orchard

• University of Waterloo

Navigation and path integration in rodents seems to involve place cells, grid cells, and theta oscillations (4–12 Hz) in the local field potential. Two main theories have been proposed to explain the neurological underpinnings of how these phenomena relate to navigation and to each other. Attractor network (AN) models revolve around the idea that l...

Some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Place cells have also been observed, firing bursts only when the animal occupies a particular region of the environment. Both of these types of cells exhibit theta-cycle modulation, firing bur...

In 2005, Hafting et al [1] reported that some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Previous to that, place cells had been observed, firing bursts only when the animal occupied a particular region of the environment. Both of these type...

Even without sensory input, an animal can estimate how far it has moved by integrating its velocity, a process called path integration. The entorhinal cortex (EC) and hippocampus seem to be involved in path integration, and in an animal’s perceived location in space. However, path integration is highly susceptible to accumulating errors. A real ani...

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response...

Abstarct: The very hot and power-hungry x-ray filaments in today's computed tomography (CT) scanners constrain their design to be big and stationary. What if we built a CT scanner that could be deployed at the scene of a car accident to acquire tomographic images before moving the victim? Recent developments in nanotechnology have shown that carbon...

The majority of image registration methods deal with registering only two images at a time. Recently, a clustering method that concurrently registers more than two multi-sensor images was proposed, dubbed ensemble clustering. In this paper, we apply the ensemble clustering method to a deformable registration scenario for the first time. Non-rigid d...

Many registration scenarios involve aligning more than just two images. These image sets-called ensembles-are conventionally registered by choosing one image as a template, and every other image is registered to it. This pairwise approach is problematic because results depend on which image is chosen as the template. The issue is particularly acute...

This paper describes an automated image restoration algorithm. The technique is based on the Stockwell transform (ST) and its discrete version, the discrete orthonormal Stockwell transform (DOST). These mathematical transforms provide a multiresolution spatial-frequency representation of a signal or image. First, we give a brief introduction to the...

Abstract Automatic,registration of multimodal,images has proven,to be a difficult task. Most existing tech- niques have difficulty dealing with situations involving highly non-homogeneous,image,contrast and a small initial overlapping,region between,the images. This pa- per presents a robust multi-resolution method,for regis- tering multimodal,imag...

In this paper, we investigate the use of the Stockwell Transform for image compression. The proposed technique uses the Discrete Orthogonal Stockwell Transform (DOST), an orthogonal version of the Discrete Stockwell Transform (DST). These mathematical transforms provide a multiresolution spatial-frequency representation of a signal or image. First,...

To register three or more images together, current approaches involve registering them two at a time. This pairwise approach can lead to registration inconsistencies. It can also result in diminished accuracy because only a fraction of the total data is being used at any given time. We propose a registration method that simultaneously registers the...

We present an efficient method for computing the discrete orthonormal Stockwell transform (DOST). The Stockwell transform (ST) is a time-frequency decomposition transform that is showing great promise in various applications, but is limited because its computation is infeasible for most applications. The DOST is a nonredundant version of the ST, so...

This paper presents a fast Fourier transform (FFT)-accelerated approach designed to handle many of the difficulties associated with the registration of optical and light detection and ranging (LIDAR) images. The proposed algorithm utilizes an exhaustive region correspondence search technique to determine the correspondence between regions of intere...

Previous efforts to compensate for patient motion in MRI invariably assume that the patient is motionless for some part of the scan. In this paper, we propose the use of motion-tracking data to enable motion-correction during the entire scan, including the acquisition stage. Using a simulated MRI scanner, we compare the different ways to use the mo...

The Stockwell Transform (ST) is a time‐frequency signal decomposition that is gaining in popularity, likely because of its direct relation with the Fourier Transform (FT). A discrete and non‐redundant version of the ST, denoted the Discrete Orthonormal Stockwell Transform (DOST), has made the use of the ST more feasible. However, the matrix multipl...

Dental features have been widely used for forensic identification purposes. However, the point-by-point comparison performed by a forensic odontologist in mass disaster situations or missing persons cases would be cumbersome and time-consuming due to the large number of records that would need to be compared. Consequently, a move towards computer-a...

This paper presents a new approach for multimodal medical image registration and compares it to normalized mutual information (NMI) and the correlation ratio (CR). Like NMI and CR, the new method's measure of registration quality is based on the distribution of points in the joint intensity scatter plot (JISP); compact clusters indicate good regist...

The very hot and power-hungry x-ray filaments in today's computed tomography (CT) scanners constrain their design to be big and stationary. What if we built a CT scanner that could be deployed at the scene of a car accident to acquire tomographic images before moving the victim? Recent developments in nanotechnology have shown that carbon nanotubes...

Nonlocal-means (NL-means) is an image denoising method that replaces each pixel by a weighted average of all the pixels in the image. Unfortunately, the method requires the computation of the weighting terms for all possible pairs of pixels, making it computationally expensive. Some short-cuts assign a weight of zero to any pixel pairs whose neighb...

This paper introduces a novel approach to the problem of image inpainting through the use of nonlocal-means. In traditional inpainting techniques, only local information around the target regions are used to fill in the missing information, which is insufficient in many cases. More recent inpainting techniques based on the concept of exemplar-based...

An image mosaic is a rendering of a large target image by arranging a collection of small source images, often in an array, each chosen specifically to fit a particular block of the target image. Most mosaicking methods are simplistic in the sense that they break the target image into regular tiles (e.g., squares or hexagons) and take extreme short...

Dental features have been widely used for forensic identification purposes. With the large number of cases that need to be investigated by forensic odontologists, a move towards computer-aided dental identification systems is necessary. We propse an automated scoring and ranking method that can be used to augment other text-based methods such as Wi...

There are many image registration situations in which the initial misalignment of the two images is large. These registration problems, often involving comparison of the two images only within a region of interest (ROI), are difficult to solve. Most intensity-based registration methods perform local optimization of their cost function and often mis...

Current multimodal registration methods almost always rely on local gradient-descent type optimization strategies. Such registration methods often converge to an incorrect local optimum, especially when the initial misregistration is large. There are monomodal image registration methods that employ global optimization techniques. This paper introdu...

Nanotechnology researchers are developing miniature, low-power X-ray devices. These innovations might revolutionize the world of computed tomography (CT). Tiny X-ray emitters and detectors could be embedded on a flexible sheet and deployed around a body part to acquire CT data at the scene of an accident. However, the irregular geometry of such a s...

The method of nonlocal-means is a powerful method for image denoising, but comes with a heavy computational price. The computation can be accelerated using the Fast Fourier Transform (FFT), yielding speed gains by a factor of 8 or more. Experiments show the benefits of the FFT in this context.

We present an efficient and accurate reconstruction technique for computed tomography (CT) images from a geometrically unconstrained set of ray sums. Current CT-scanners are immobile. How- ever, a new era in x-ray production could usher in new, lightweight, flexible and portable x-ray devices. The proposed device, currently under development, is en...

Multimodal image registration is a difficult problem in both medical imaging and remote sensing. The least-squares cost function has generally been overlooked for multimodal registration problems due to an underlying assumption that the two images being registered must have corresponding intensities. More recently, methods that employ the least-squ...

One of the major problems facing medical imaging is the presence of geometric distortions inherent in an imaging technique. Image registration techniques are often used to correct for such geometric perturbations. Recently, it was proposed that the SSD cost function can be evaluated efficiently using the Fast Fourier Transform (FFT) to determine th...

In image registration, similarity metrics are used to determine the optimal alignment between two images. A common metric used for judging image similarity is the weighted sum of squared differenc es (SSD) cost function. Recently, it was demonstrated that the evaluation of the SSD cost function can be perf ormed efficiently using the Fast Fourier T...

The weighted sum of squared di erences cost function is of-ten minimized to align two images with overlapping fields of view. If one image is shifted with respect to the other, the cost function can be written as a sum involving convolutions. This paper demonstrates that performing these convolutions in the frequency domain saves a signifi-cant amo...

In image deformation, one of the challenges is to produce a deformation that preserves image topology. Such deformations are called "homeomorphic". One method of producing homeomorphic deformations is to move the pixels according to a continuous velocity field defined over the image. The pixels flow along solution curves. Finding the pixel tra-ject...

The presence of cerebral activation may bias motion correction estimates when registering FMRI time series. This problem may be solved through the use of specific registration methods, which incorporate or down-weight cerebral activation confounding signals during registration. In this paper, we evaluate the performance of different registration me...

It has recently been shown that greater accuracy in fMRI processing can be achieved if registration and activation detection are solved simultaneously rather than in sequence. However, this simultaneous solution has been demonstrated only for fMRI experiments in which a single stimulus condition was used. This paper presents results obtained by app...

Registration using the least-squares cost function is sensitive to the intensity fluctuations caused by the blood oxygen level dependent (BOLD) signal in functional MRI (fMRI) experiments, resulting in stimulus-correlated motion errors. These errors are severe enough to cause false-positive clusters in the activation maps of datasets acquired from...

Most intensity-based fMRI registration methods do not ac- count for the fact that the volumes being aligned may differ: one may have blood oxygen level dependent (BOLD) contrast while the other does not. Especially in least-squares registration, this can result in motion pa- rameter errors that are correlated to the stimulus. An iterative technique...

It has been shown that the presence of a blood oxygen level dependent (BOLD) signal in high-field (3T and higher) fMRI datasets can cause stimulus-correlated registration errors, especially when using a least-squares registration method. These errors can result in systematic inaccuracies in activation detection. The authors have recently proposed a...

This paper looks at the difficulties that can confound published T1-weighted Magnetic Resonance Imaging (MRI) brain segmentation methods, and compares their strengths and weaknesses. Using data from the Internet Brain Segmentation Repository (IBSR) as a gold standard, we ran three different segmentation methods with and without correcting for inten...

Other researchers have proposed that the brain parenchymal fraction (or brain atrophy) may be a good surrogate measure for disease progression in patients with Multiple Sclerosis. This paper considers various factors influencing the measure of the brain parenchymal fraction obtained from dual spin-echo PD and T2-weighted head MRI scans. We investig...

The presence of BOLD contrast in M R I studies has been shown to interfere with least squares motion correction algorithms. We derive a theoretical expression for the error that activation contributes to least squares motion correction. These estimates match errors generated by motion correction experiments done on a simulated fMRl dataset. The

Other researchers have proposed that the brain parenchymal fraction (or brain atrophy) may be a good surrogate measure for disease progression in patients with multiple sclerosis. This paper considers various factors influencing the measure of the brain parenchymal fraction obtained from head MRI scans. An automatic segmentation method for the brai...

When it comes to multimodal image registration, mutual information (MI) seems to hold the biggest market share. However, MI has a number of serious flaws, not the least of which is the quantization effect caused by histogram binning. We propose a novel registration method that, like MI, is motivated by the distribution of points in the joint intens...

Similar in nature to an image mosaic, a photo-stencil is a ren-dering of a binary target image by an arrangement of smaller binary stencil images. This paper presents a method for effi-ciently creating photo-stencil images, making use of the Fast Fourier Transform to speed up costly computations. The re-sulting photo-stencils are a new and interest...