Automated analysis and visualization of preclinical whole-body microCT data

In this thesis, several strategies are presented that aim to facilitate the analysis and visualization of whole-body in vivo data of small animals. Based on the particular challenges for image processing, when dealing with whole-body follow-up data, we addressed several aspects in this thesis. The developed methods are tailored to handle data of subjects with significantly varying posture and address the large tissue heterogeneity of entire animals. In addition, we aim to compensate for lacking tissue contrast by relying on approximation of organs based on an animal atlas. Beyond that, we provide a solution to automate the combination of multimodality, multidimensional data.* Advanced School for Computing and Imaging (ASCI), Delft, NL * Bontius Stichting inz Doelfonds Beeldverwerking, Leiden, NL * Caliper Life Sciences, Hopkinton, USA * Foundation Imago, Oegstgeest, NLUBL - phd migration 201

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

Interactive navigation of segmented MR angiograms using simultaneous curved planar and volume visualizations

Purpose \ud Interactive visualization is required to inspect and monitor the automatic segmentation of vessels derived from contrast-enhanced magnetic resonance angiography (CE-MRA). A dual-view visualization scheme consisting of curved planar reformation (CPR) and direct volume rendering (DVR) was developed for this purpose and tested. \ud \ud Methods \ud A dual view visualization scheme was developed using the vessel pathline for both camera position and rotation in 3D, greatly reducing the degrees of freedom (DOF) required for navigation. Pathline-based navigation facilitates coupling of the CPR and DVR views, as local position and orientation can be matched precisely. The new technique was compared to traditional techniques in a user study. Layperson users were required to perform a visual search task that involves checking for (minor) errors in segmentations of MRA data from a software phantom. The task requires the user to examine both views. \ud \ud Results \ud Pathline-based navigation and coupling of CPR and DVR provide user speed performance improvements in a vessel inspection task. Interactive MRA visualization with this method, where rotational degrees of freedom were reduced, had no negative effect. \ud \ud Conclusions \ud The DOF reduction achieved by the new navigation technique is beneficial to user performance. The technique is promising and merits comprehensive evaluation in a realistic clinical setting

Neuroinformatics in Functional Neuroimaging

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology