Multi-scale active shape description in medical imaging

Shape description in medical imaging has become an increasingly important research field in recent years. Fast and high-resolution image acquisition methods like Magnetic Resonance (MR) imaging produce very detailed cross-sectional images of the human body - shape description is then a post-processing operation which abstracts quantitative descriptions of anatomically relevant object shapes. This task is usually performed by clinicians and other experts by first segmenting the shapes of interest, and then making volumetric and other quantitative measurements. High demand on expert time and inter- and intra-observer variability impose a clinical need of automating this process. Furthermore, recent studies in clinical neurology on the correspondence between disease status and degree of shape deformations necessitate the use of more sophisticated, higher-level shape description techniques. In this work a new hierarchical tool for shape description has been developed, combining two recently developed and powerful techniques in image processing: differential invariants in scale-space, and active contour models. This tool enables quantitative and qualitative shape studies at multiple levels of image detail, exploring the extra image scale degree of freedom. Using scale-space continuity, the global object shape can be detected at a coarse level of image detail, and finer shape characteristics can be found at higher levels of detail or scales. New methods for active shape evolution and focusing have been developed for the extraction of shapes at a large set of scales using an active contour model whose energy function is regularized with respect to scale and geometric differential image invariants. The resulting set of shapes is formulated as a multiscale shape stack which is analysed and described for each scale level with a large set of shape descriptors to obtain and analyse shape changes across scales. This shape stack leads naturally to several questions in regard to variable sampling and appropriate levels of detail to investigate an image. The relationship between active contour sampling precision and scale-space is addressed. After a thorough review of modem shape description, multi-scale image processing and active contour model techniques, the novel framework for multi-scale active shape description is presented and tested on synthetic images and medical images. An interesting result is the recovery of the fractal dimension of a known fractal boundary using this framework. Medical applications addressed are grey-matter deformations occurring for patients with epilepsy, spinal cord atrophy for patients with Multiple Sclerosis, and cortical impairment for neonates. Extensions to non-linear scale-spaces, comparisons to binary curve and curvature evolution schemes as well as other hierarchical shape descriptors are discussed

Surface and Volumetric Segmentation of Complex 3-D Objects Using Parametric Shape Models

The problem of part definition, description, and decomposition is central to the shape recognition systems. In this dissertation, we develop an integrated framework for segmenting dense range data of complex 3-D scenes into their constituent parts in terms of surface and volumetric primitives. Unlike previous approaches, we use geometric properties derived from surface, as well as volumetric models, to recover structured descriptions of complex objects without a priori domain knowledge or stored models. To recover shape descriptions, we use bi-quadric models for surface representation and superquadric models for object-centered volumetric representation. The surface segmentation uses a novel approach of searching for the best piecewise description of the image in terms of bi-quadric (z = f(x,y)) models. It is used to generate the region adjacency graphs, to localize surface discontinuities, and to derive global shape properties of the surfaces. A superquadric model is recovered for the entire data set and residuals are computed to evaluate the fit. The goodness-of-fit value based on the inside-outside function, and the mean-squared distance of data from the model provide quantitative evaluation of the model. The qualitative evaluation criteria check the local consistency of the model in the form of residual maps of overestimated and underestimated data regions. The control structure invokes the models in a systematic manner, evaluates the intermediate descriptions, and integrates them to achieve final segmentation. Superquadric and bi-quadric models are recovered in parallel to incorporate the best of the coarse-to-fine and fine-to-coarse segmentation strategies. The model evaluation criteria determine the dimensionality of the scene, and decide whether to terminate the procedure, or selectively refine the segmentation by following a global-to-local part segmentation approach. The control module generates hypotheses about superquadric models at clusters of underestimated data and performs controlled extrapolation of the part-model by shrinking the global model. As the global model shrinks and the local models grow, they are evaluated and tested for termination or further segmentation. We present results on real range images of scenes of varying complexity, including objects with occluding parts, and scenes where surface segmentation is not sufficient to guide the volumetric segmentation. We analyze the issue of segmentation of complex scenes thoroughly by studying the effect of missing data on volumetric model recovery, generating object-centered descriptions, and presenting a complete set of criteria for the evaluation of the superquadric models. We conclude by discussing the applications of our approach in data reduction, 3-D object recognition, geometric modeling, automatic model generation. object manipulation, and active vision

Urban identity through quantifiable spatial attributes: coherence and dispersion of local identity through the automated comparative analysis of building block plans

This analysis investigates whether and to what degree quantifiable spatial attrib-utes, as expressed in plan representations, can capture elements related to the ex-perience of spatial identity. By combining different methods of shape and spatial analysis it attempts to quantify spatial attributes, predominantly derived from plans, in order to illustrate patterns of interrelations between spaces through an ob-jective automated process. The study focuses on the scale of the urban block as the basic modular unit for the formation of urban configurations and the issue of spa-tial identity is perceived through consistency and differentiation within and amongst urban neighbourhoods

Contextualizing phenomenology in event management research: Deciphering the meaning of event experiences

Purpose - Although the core phenomenon of events is the experiences and the meanings attached to them, there is limited management research on the experiential, existential and ontological dimensions of events. Phenomenology provides a sound philosophical framework for studying the multifaceted dimensions of experiences and associated meanings of events. However, quite surprisingly, phenomenology has not yet been systematically applied on the event management field. This conceptual paper aims to introduce phenomenology to the study of events, demonstrate its value for the field and encourage as well as guide its application on event management research. Design/methodology/approach - A review and synthesis of the main phenomenological streams of thought was undertaken in order to develop a research paradigm for the application of phenomenology on the event management field. Findings - The paper explains why phenomenology is needed in the study of events and their management, its conceptual underpinnings and streams of thought and finally suggests a research framework for conducting phenomenological studies in event management. Research limitations/implications - The consequences of the phenomenological perspective are delineated for explaining how the study of event meanings and experiences can be undertaken from this perspective. The limitations of phenomenology are noted such as the emphasis on ‘lifeworld’ subjectivity and subsequent difficulty to claim the generalizability of research findings. Practical implications - The suggested research framework can guide future event management research on how to apply phenomenology to the study of event experiences and meanings. On this basis, practitioners can get insight regarding how to develop and design events that optimize the perceived experiences of attendees. Originality/value - While the experiential paradigm and the phenomenological turn have been spread across many disciplines emphasizing the essence of lived experiences in a variety of human interactions and exchanges, the event management field lags behind. This is unfortunate and has to be addressed as the experiences and meanings shape the essence of events. Therefore, this conceptual paper hopes to inspire, encourage and guide event management researchers to embrace and apply the phenomenological perspective on their future research endeavors, which can profitably complement and expand the predominant research paradigms in the field

There is Nothing It is Like to See Red: Holism and Subjective Experience

The Nagel inspired “something-it-is-like” (SIL) conception of conscious experience remains a dominant approach in philosophy. In this paper I criticize a prevalent philosophical construal of SIL consciousness, one that understands SIL as a property of mental states rather than entities as a whole. I argue against thinking of SIL as a property of states, showing how such a view is in fact prevalent, under-warranted, and philosophically pernicious in that it often leads to an implausible reduction of conscious experience to qualia. I then develop a holistic conception of SIL for entities (not states) and argue that it has at least equal pre-empirical warrant, is more conservative philosophically in that it decides less from the a priori “armchair,” and enjoys a fruitful two-way relationship with empirical work

A unified framework for building ontological theories with application and testing in the field of clinical trials

The objective of this research programme is to contribute to the establishment of the emerging science of Formal Ontology in Information Systems via a collaborative project involving researchers from a range of disciplines including philosophy, logic, computer science, linguistics, and the medical sciences. The re­searchers will work together on the construction of a unified formal ontology, which means: a general framework for the construction of ontological theories in specific domains. The framework will be constructed using the axiomatic-deductive method of modern formal ontology. It will be tested via a series of applications relating to on-going work in Leipzig on medical taxonomies and data dictionaries in the context of clinical trials. This will lead to the production of a domain-specific ontology which is designed to serve as a basis for applications in the medical field