Description
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A novel automated approach of multi-modalitybiomedical image control point detection,registration, and fusion has been successfullydeveloped. The new algorithm, which consists of theAdaptive Exploratory Algorithm for the controlpoint/feature detection and Heuristic OptimizationAlgorithm, is reliable and time efficient. The newapproach has been applied on three ophthalmologicmodalities of nonhuman primate eyes - angiogram,fundus, and oxygen saturation retinal images. It hasachieved an excellent result by giving thevisualization of fundus or oxygen saturation imagewith a complete angiogram overlay. By locking themulti-sensor retinal images in one place, thealgorithm allows ophthalmologists to match the sameeye over time to get a sense of disease progress andpinpoint surgical tools. The new registration andfusion algorithm can be easily expanded to the eye,brain, or body images of human or animals'. Thetarget readers are graduate/undergraduate students,faculty, and research scientists who are interestedin the image registration and fusion algorithms;ophthalmologists and physicians; image processingsoftware developers; and whoever wants to learn imagefusion.
(Author portrait)
Cao Hua Hua Cao is a Senior Research Scientist in the Computer Scienceand Ophthalmology Dept. of Louisiana State University, USA. Shereceived B.E. of Information Science in 2000, M.S. of SystemsScience in 2003, and Ph.D. of Computer Science in 2008. Herresearch interests include biomedical imaging, featureextraction, and image registration and fusion.
