published_or_final_version / Medicine / Doctoral / Doctor of Philosophy

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.