Visualization and Haptics for Interactive Medical Image Analysis

• Main Author: Vidholm, Erik
• Format: Doctoral Thesis
• Language: English
• Published: Uppsala universitet, Centrum för bildanalys 2008
• Subjects: Bildanalys; medical image analysis; haptic rendering; volume visualization; interactive segmentation
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8409; http://nbn-resolving.de/urn:isbn:978-91-554-7067-8

Modern medical imaging techniques provide an increasing amount of high-dimensional and high-resolution image data that need to be visualized, analyzed, and interpreted for diagnostic and treatment planning purposes. As a consequence, efficient ways of exploring these images are needed. In order to work with specific patient cases, it is necessary to be able to work directly with the medical image volumes and to generate the relevant 3D structures directly as they are needed for visualization and analysis. This requires efficient tools for segmentation, i.e., separation of objects from each other and from the background. Segmentation is hard to automate due to, e.g., high shape variability of organs and limited contrast between tissues. Manual segmentation, on the other hand, is tedious and error-prone. An approach combining the merits from automatic and manual methods is semi-automatic segmentation, where the user interactively provides input to the methods. For complex medical image volumes, the interactive part can be highly 3D oriented and is therefore dependent on the user interface. This thesis presents methods for interactive segmentation and visualization where true 3D interaction with haptic feedback and stereo graphics is used. Well-known segmentation methods such as fast marching, fuzzy connectedness, live-wire, and deformable models, have been tailored and extended for implementation in a 3D environment where volume visualization and haptics are used to guide the user. The visualization is accelerated with graphics hardware and therefore allows for volume rendering in stereo at interactive rates. The haptic feedback is rendered with constraint-based direct volume haptics in order to convey information about the data that is hard to visualize and thereby facilitate the interaction. The methods have been applied to real medical images, e.g., 3D liver CT data and 4D breast MR data with good results. To provide a tool for future work in this area, a software toolkit containing the implementations of the developed methods has been made publicly available.