Development of novel algorithm to visualize blood vessels on 3D ultrasound images during liver surgery
Volume visualization is a method that displays three-dimensional (3D) data in two-dimensional (2D) space. Using 3D datasets instead of 2D traditional images improves the visualization of anatomical structures, and volume visualization helps radiologists and surgeons to review large datasets comprehensively so that diagnosis and treatment can be enhanced. In liver surgery, blood vessel detection is important. Liver vessels have various shapes and due to the presence of noise in the ultrasound images, they can be confused with noise. Suboptimal images can sometimes lead to surgical errors where the surgeon may cut the blood vessel in error. The ultrasound system is versatile and portable and has the advantage of being able to be used in the operating theatre. Due to the nature of B-mode ultrasound, 1-D transfer function volume visualization of images cannot abrogate shadow artifacts. While multi-dimensional transfer function improves the ability to define features of interest, the high dimensionality in the parameter domain renders it unwieldy and difficult for clinicians to work with. To overcome these limitations, an algorithm for volume visualization that can provide effective 3D visualization of noisy B-mode ultrasound images, which can be useful for clinicians, is proposed. We propose a method that is appropriate for liver ultrasound images focusing on vessels and tumors (if present) in order to delineate their structure and positions clearly to preempt surgical error during operation. This method can prevent possible errors during liver surgery by providing more detailed high quality 3D images for clinicians. Key Words: Visualization, 3D ultrasound image, Volume Rendering, Liver surgery, Liver vessels.
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