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6 April 2005 Visualizing blood vessel trees in three dimensions: clinical applications
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Abstract
A connected network of blood vessels surrounds and permeates almost every organ of the human body. The ability to define detailed blood vessel trees enables a variety of clinical applications. This paper discusses four such applications and some of the visualization challenges inherent to each. Guidance of endovascular surgery: 3D vessel trees offer important information unavailable by traditional x-ray projection views. How best to combine the 2- and 3D image information is unknown. Planning/guidance of tumor surgery: During tumor resection it is critical to know which blood vessels can be interrupted safely and which cannot. Providing efficient, clear information to the surgeon together with measures of uncertainty in both segmentation and registration can be a complex problem. Vessel-based registration: Vessel-based registration allows pre-and intraoperative images to be registered rapidly. The approach both provides a potential solution to a difficult clinical dilemma and offers a variety of visualization opportunities. Diagnosis/staging of disease: Almost every disease affects blood vessel morphology. The statistical analysis of vessel shape may thus prove to be an important tool in the noninvasive analysis of disease. A plethora of information is available that must be presented meaningfully to the clinician. As medical image analysis methods increase in sophistication, an increasing amount of useful information of varying types will become available to the clinician. New methods must be developed to present a potentially bewildering amount of complex data to individuals who are often accustomed to viewing only tissue slices or flat projection views.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elizabeth Bullitt and Stephen Aylward "Visualizing blood vessel trees in three dimensions: clinical applications", Proc. SPIE 5749, Medical Imaging 2005: Image Perception, Observer Performance, and Technology Assessment, (6 April 2005); https://doi.org/10.1117/12.604746
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