Peter H. Gregson

Wavelet-based image registration and segmentation framework for the quantitative evaluation of hydrocephalus

Hydrocephalus, characterized by increased fluid in the cerebral ventricles, is traditionally evaluated by a visual assessment of serial CT scans. The complex shape of the ventricular system makes accurate visual comparison of CT scans difficult. The current research developed a quantitative method to measure the change in cerebral ventricular volume over time. Key elements of the developed framework are: adaptive image registration based on mutual information and wavelet multiresolution analysis; adaptive segmentation with novel feature extraction based on the Dual-Tree Complex Wavelet Transform; volume calculation. The framework, when tested on physical phantoms, had an error of 2.3%. When validated on clinical cases, results showed that cases deemed to be normal/stable had a calculated volume change less than 5%. Those with progressive/treated hydrocephalus had a calculated change greater than 20%. These findings indicate that the framework is reasonable and has potential for development as a tool in the evaluation of hydrocephalus.

Selecting and Assessing Quantitative Early Ultrasound Texture Measures for Their Association With Cerebral Palsy

Cerebral palsy (CP) develops as a consequence of white matter damage (WMD) in approximately one out of every 10 very preterm infants. Ultrasound (US) is widely used to screen for a variety of brain injuries in this patient population, but early US often fails to detect WMD. We hypothesized that quantitative texture measures on US images obtained within one week of birth are associated with the subsequent development of CP. In this retrospective study, using images from a variety of US machines, we extracted unique texture measures by means of adaptive processing and high resolution feature enhancement. We did not standardize the images, but used patients as their own controls. We did not remove speckle, as it may contain information. To test our hypothesis, we used the ldquorandom forestrdquo algorithm to create a model. The random forest classifier achieved a 72% match to the health outcome of the patients (CP versus no CP), whereas designating all patients as having CP would have resulted in 53% error. This suggests that quantitative early texture measures contain diagnostic information relevant to the development of CP.

Resting muscle sounds in anesthetized patients

It is known that contracting muscle makes low frequency sound vibrations. Small vibrations of uncertain origin are found over resting muscle. These could be shown to be of muscle origin if they significantly diminish in response to agents expected to decrease muscle activity. Thiopental, propofol, and neuromuscular-junction blocking muscle relaxants have such properties. Twenty-one subjects slated for elective surgery for which they would routinely be anesthetized and paralysed gave informed consent to having a small accelerometer taped upon their supine biceps (9 subjects), or volar forearm (12 subjects). Recordings were made in four stages while subjects: (i) lifted a 2-kg weight just off the sponge armrest on which their outstretched arm lay; (ii) relaxed their arm in the awake state prior to anesthesia; (iii) had anesthesia induced with intravenous thiopental (n = 11) or propofol (n = 10); and (iv) were paralysed. Recordings were digitised at 172-Hz and 6-s segments fast Fourier transformed (FFT). Total signal power, as determined by the area under the power spectrum, was significantly different (p < 0.05) in all stages for the biceps and in all but stages (iii) from (iv) in the forearm. It appears that resting muscle generates measurable vibrations.

Using the local mode for edge detection in ultrasound images

We are investigating quantitative ultrasound texture measures as an additional source of diagnostic information for the detection of white matter damage in very preterm infants. White matter damage is a form of brain damage which leads to cerebral palsy. Ultrasound speckle properties have been shown to correlate to scatterer properties in phantoms. The disease process alters the scatterer type and density in white matter. We are enhancing speckle edges in cranial ultrasound images to determine if local speckle gradients and speckle edge densities correlate to patient outcome. Speckle edges are very diffuse and traditional edge enhancing schemes, such as Sobel, do not perform well. To capture the speckle edge detail, we use film images scanned at a very high resolution. The digitization introduces a significant noise component and does not suppress the ultrasound film grain. We present a non-linear filter to enhance the speckle edge information. The filter (DM) exploits the changes to speckle edges that result from applying local mode filtering. This technique has the advantages of maintaining edge center localization with large window sizes and performing better than Sobel for diffuse edges. In this work, we discuss the filter, its parameters, and their selection for a given application

Automated registration of multimodal brain image sets using computer vision methods

We present a new method of registering three dimensional image volumes of the brain of a given patient acquired at different times or with different imaging modalities, or both. Registration is an essential requirement for fusing the data from the two image sets so as to either increase the available information by exploiting complementary imaging modalities, or to measure small changes over time for prognostication, disease assessment, etc. The new technique exploits an external, removable, remountable reference frame which is attached to the head. Computer vision techniques are used to determine the positions of fiducial marks in every image. The transformation required to map each image of one image volume onto the other image volume is developed using the theory of quaternions. The results indicate that the new technique is robust and practical in a clinical setting.

Ultrasonic tissue characterization as a predictor of white matter damage: results of a preliminary study

Premature infants are prone to white matter damage (WMD), which is associated with cerebral palsy (CP) and cognitive impairment. Ultrasound (US) is the preferred imaging modality to detect WMD. To improve on existing diagnostic rates, quantitative measures incorporating new information are needed. We are investigating US texture measures as new indicators of white matter health. We have developed algorithms to enhance texture features and then obtain a measure of the tissue texture. Using our texture measures, data from 18 patients (12 with normal outcome, 6 who developed CP) form separate populations based on patient outcome. Our algorithms are applied to B-mode cranial US images without compensating for operator-dependent machine settings and without suppressing speckle. The results of the preliminary study are intended to form the basis for the design of a computer aided diagnosis system for the early detection of white matter damage.

A control continuum for tetherless underwater vehicles

There exists a need for a new class of underwater vehicle that can perform both close control tasks as well as long-range exploration without manual reconfiguration. A tetherless underwater vehicle (TUV) with acoustic communications to an operator station has potential to fulfill this need. The problem with TUVs is the limited communications bandwidth and time lag increasing with range. This research presents a new class of controller for TUVs that isolates the operator from the time-varying lag. This isolation is accomplished through various means such as predictive control and automatic waypoint creation and tracking. A continuum of control is formed with these various paradigms and a smooth evolution through the continuum is formulated, based on the measured time delay.

Determination of Coordinate System in Short-Axis View of Left Ventricle

With the increasing rate of myocardial infarction (MI) in men and women, it is important to develop a diagnosis tool to determine the effect of MI on the mechanics of the heart and to minimize the effect of heart muscle damage on overall cardiac performance. After a myocardial infarct, the left ventricle of the heart enlarges to compensate for a weak heart muscle. The enlarged and weakened heart gives rise to the clinical syndrome of heart failure. In order to maximize the mechanical performance of the weakened heart, regional ventricular loading and contraction must be understood. To isolate regional wall mechanics, a floating centroid for the left ventricle must to be calculated. This is easy in the normal heart where the left ventricle approximates a single radius of curvature; however in heart failure there are irregular shape changes that complicate this calculation. The conventional method used for centroid calculation employs a center of mass (COM) determination of the whole left ventricle. This method has many shortcomings when applied to an enlarged and irregular left ventricle. This paper proposes a new algorithm for centroid calculation based on iterative majorization to locate the centroid.

A New Numerical Scheme for Anisotropic Diffusion

Automatically stopping the diffusion process is a challenging task in anisotropic diffusion (AD). Without a preset number of iterations, over-smoothing of semantically meaningful features occurs very easily with current discrete version of AD (DAD). We address this problem by considering the difference in the behavior of DAD and its continuous counterpart. A new numerical scheme is proposed in this paper in which the non-negative part of the derivative of flux is employed for the first time to control the smoothing strength. Our proposed algorithm implements the desired AD operation with over-smoothing prevented.

Transfer-function analysis in anesthesia research.

ConclusionsDr Fujiwara’s paper introduces a potentially-important scientific technique to our specialty. Transferfunction analysis holds promise of clarifying why so many of the drugs that we inject or vaporise alter the respiratory, cardiovascular and nervous systems in the way they do.ConclusionL’article du docteur Fujiwara présente une technique scientifique potentiellement importante. L’analyse de la fonction de transfert est prometteuse, car elle pourrait expliquer pourquoi tant de médicaments injectés ou vaporisés modifient les systèmes respiratoire, cardiovasculaire et nerveux comme ils le font.