Perfusion-weighted computed tomography (CTP) is a relatively recent innovation that estimates a value for cerebral blood flow (CBF) using a series of axial head CT images which tracks the time course ...of signal from an administered bolus of intravenous contrast. We introduce a novel computer-based method for objective quantification of CBF values calculated from CTP images. Our method corrects for the inherent variability of the CTP methodology seen in the subarachnoid hemorrhage (SAH) patient population to potentially aid in the diagnosis of cerebral vasospasm (CVS). This method analyzes and quantifies side-to-side asymmetry of CBF and represents relative differences in a construct termed a relative difference map (RDM). Herein, we present our preliminary results that show that analysis of histograms of the RDM in left and right hemispheres, as well as different vascular territories of the brain, can be used for detection and diagnosis of cerebral vasospasm in patients with SAH. While this method has been designed specifically to analyze postprocessed CTP images, it could be potentially applied to quantification and analysis of MR perfusion data, as well.
MADAPT Liu, Robin; Gibbs, Celina; Coady, Yvonne
ACM International Conference Proceeding Series; Vol. 80: Proceedings of the 3rd workshop on Adaptive and reflective middleware; 19-19 Oct. 2004,
10/2004
Conference Proceeding
An increasingly significant cost associated with dynamically adaptive middleware is the complexity of managing the code responsible for adaptive behaviour. It is not surprising that, due to the ...fine-grained nature of trace-data collection and the subtle adaptation that can result, more flexible systems are typically more complex to manage. This paper makes the case for using aspect-oriented programming (AOP) 6 as a means to achieve adaptive middleware based on fine-grained, customizable, profiling techniques. A feasibility-study combining Java Management Extensions (JMX) 3 and AOP shows the effectiveness of the synergy between the management support for application services offered by JMX, and the structured support for crosscutting concerns offered by AOP.
We propose a novel method to automatically compute the symmetry plane and correct the 3D orientation of patient brain images. Many images of the brain are clinically unreadable because of the ...misalignment of the patient's head in the scanner. We proposed an algorithm that represents the brain volume as a re-parameterized surface point cloud where each location has been parameterized by its elevation (latitude), azimuth (longitude) and radius. The removal of the interior contents of the brain makes this approach perform robustly in the presence of the brain pathologies, e.g. tumor, stroke and bleed. Thus, we decompose the symmetry plane computation problem into a surface matching routine. The search for the best matching surface is implemented in a multi-resolution paradigm so as to decrease computational time considerably. Spatial affine transform then is performed to rotate the 3D brain images and align them within the coordinate system of the scanner. The corrected brain volume is re-sliced such that each planar image represents the brain at the same axial level
We propose a framework of multi-modality brain registration methods using symmetry plane as the principal feature for geometric matching. By bringing the symmetry plane of two rigid objects into ...coincidence, we can potentially match two objects approximately if there is no apparent elastic distortion. We illustrated this concept using Visible Human dataset, that included color cryosection, and radiological data, from which we extracted 3D mesh models of skin, brain and skull, and aligned them into nested bodies. Each model was generated with different spatial orientation and resolution, and their alignment, was guided by the underlying anatomical relationships in the head region, and a requirement, by an application that the meshes didn 't intersect. After alignment of the symmetry planes, obtained for each mesh using spatial affine transformations, the further geometric adjustment, to achieve complete registration of the nested models, is confined within a 2D plane (i.e. the symmetry plane). This simple method of registration of mesh anatomical models, has a potential to significantly reduce the degrees of freedom in various 3D brain registration applications. It can be also treated as a pre-registration operation before applying other registration methods.
Statistical Bilateral Asymmetry Measurement in Brain Images Xin Liu; Ogden, R.T.; Imielinska, C. ...
2006 International Conference of the IEEE Engineering in Medicine and Biology Society,
2006, Letnik:
2006
Conference Proceeding, Journal Article
We present an improvement of an automated generic methodology for symmetry identification, asymmetry quantification, and segmentation of brain pathologies, utilizing the inherent bi-fold mirror ...symmetry in brain imagery. In the pipeline of operations starting with detection of the symmetry axis, hemisphere-wise cross registration, statistical correlation and quantification of asymmetries, we segment a target brain pathology. The detection of pathological difference left to right in brain imagery is complicated by normal variations as well as geometric misalignment in anatomical structures between two hemispheres. Introducing hemisphere-wise registration and spatial correlation makes our approach perform robustly in the presence of normal asymmetries and systematic artifacts such as bias field and acquisition noise
Classification of human brain pathologies can be guided by the estimation of the departure of 3D internal structures from the normal bilateral symmetry. However symmetry based analysis can't be ...precisely carried out when the 3D brain orientation is misaligned, a common occurrence in clinical practice. In this paper, a technique to automatically identify the symmetry plane and correct the 3D orientation of volumetric brain images in a cost effective way is developed. The algorithm seeks the best sampling strategies to realign 3D volumetric representation of the brain within scanner coordinate system. The inertia matrix is computed on the sampled brain, and the principle axes are derived from the eigenvectors of the inertia matrix. The technique is demonstrated on MR and CT brain images and the detected symmetry plane that is orthogonal to the principle vectors is provided. A spatial affine transform is applied to rotate the 3D brain images and align them within the coordinate system of the scanner. The corrected brain volume is re-sliced such that each planar image represents the brain at the same axial level.
Safe and Sound Evolution with SONAR Liu, Chunjian Robin; Gibbs, Celina; Coady, Yvonne
Transactions on Aspect-Oriented Software Development IV
Book Chapter
Traditional diagnostic and optimization techniques typically rely on static instrumentation of a small portion of an overall system. Unfortunately, solely static and localized approaches are simply ...no longer sustainable in the evolution of today’s complex and dynamic systems. Sustainable Optimization and Navigation with Aspects for system-wide Reconciliation is a fluid and unified framework that enables stakeholders to explore and adapt meaningful entities that are otherwise spread across predefined abstraction boundaries. Through a combination of Aspect-Oriented Programming, Extensible Markup Language, and management tools such as Java Management Extensions, SONAR can comprehensively coalesce scattered artifacts—enabling evolution to be more inclusive of system-wide considerations by supporting both iterative and interactive practices. We believe this system-wide approach promotes the application of safe and sound principles in system evolution. This paper presents SONAR’s model, examples of its concrete manifestation, and an overview of its associated costs and benefits. Case studies demonstrate how SONAR can be used to accurately identify performance bottlenecks and effectively evolve systems by optimizing behaviour, even at runtime.
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