To aid diagnosis, treatment planning, and patient education, clinicians require tools to anal- yse and explore the increasingly large three-dimensional (3-D) datasets generated by modern medical scanners. Direct volume rendering is one such tool finding favour with radiologists and surgeons for its photorealistic representation. More recently, volume illustration — or non-photorealistic rendering (NPR) — has begun to move beyond the mere depiction of data, borrowing concepts from illustrators to visually enhance desired information and suppress un- wanted clutter. Direct volume rendering generates images by accumulating pixel values along rays cast into a 3-D image. Transfer functions allow users to interactively assign material properties such as colour and opacity (a process known as classification). To achieve real-time framerates, the rendering must be accelerated using a technique such as 3-D texture mapping on commod- ity graphics processing units (GPUs). Unfortunately, current methods do not allow users to intuitively enhance regions of interest or suppress occluding structures. Furthermore, addi- tional scalar images describing clinically relevant measures have not been integrated into the direct rendering method. These tasks are essential for the effective exploration, analysis, and presentation of 3-D images. This body of work seeks to address the aforementioned limitations. First, to facilitate the research program, a flexible architecture for prototyping volume illustration methods is pro- posed. This program unifies a number of existing techniques into a single framework based on 3-D texture mapping, while also providing for the rapid experimentation of novel methods. Next, the prototyping environment is employed to improve an existing method—called tagged volume rendering — which restricts transfer functions to given spatial regions using a number of binary segmentations (tags). An efficient method for implementing binary tagged volume rendering is presented, along with various technical considerations for improving the classifi- cation. Finally, the concept of greyscale tags is proposed, leading to a number of novel volume visualisation techniques including position modulated classification and dynamic exploration. The novel methods proposed in this work are generic and can be employed to solve a wide range of problems. However, to demonstrate their usefulness, they are applied to a specific case study. Ischaemic heart disease, caused by narrowed coronary arteries, is a leading healthconcern in many countries including Australia. Computed tomography angiography (CTA) is an imaging modality which has the potential to allow clinicians to visualise diseased coronary arteries in their natural 3-D environment. To apply tagged volume rendering for this case study, an active contour method and minimal path extraction technique are proposed to segment the heart and arteries respectively. The resultant images provide new insight and possibilities for diagnosing and treating ischaemic heart disease.

Le Doppler ultrasensible est une nouvelle technique d'imagerie ultrasonore permettant d'observer les flux sanguins avec une résolution très fine et sans agent de contraste. Appliquée à l'imagerie microvasculaire cérébrale des rongeurs, cette méthode produit de très fines cartes vasculaires 3D du cerveau à haute résolution spatiale. Ces réseaux vasculaires contiennent des structures tubulaires caractéristiques qui pourraient servir de points de repère pour localiser la position de la sonde ultrasonore et tirer parti des avantages pratiques des appareils à ultrason. Ainsi, nous avons développé un premier système de neuronavigation chez les rongeurs basé sur le recalage automatique d'images cérébrales. En utilisant des méthodes d’extraction de chemins minimaux, nous avons développé une nouvelle méthode isotrope de segmentation pour l’analyse géométrique des réseaux vasculaires en 3D. Cette méthode a été appliquée à la quantification des réseaux vasculaires et a permis le développement d'algorithmes de recalage de nuages de points pour le suivi temporel de tumeurs. / Ultrasensitive Doppler is a new ultrasound imaging technique allowing the observation of blood flows with a very fine resolution and no contrast agent. Applied to cerebral microvascular imaging in rodents, this method produces very fine vascular 3D maps of the brain at high spatial resolution. These vascular networks contain characteristic tubular structures that could be used as landmarks to localize the position of the ultrasonic probe and take advantage of the easy-to-use properties of ultrasound devices such as low cost and portability. Thus, we developed a first neuronavigation system in rodents based on automatic registration of brain images. Using minimal path extraction methods, we developed a new isotropic segmentation framework for 3D geometric analysis of vascular networks (extraction of centrelines, diameters, curvatures, bifurcations). This framework was applied to quantify brain and tumor vascular networks, and finally leads to the development of point cloud registration algorithms for temporal monitoring of tumors.