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A novel automated approach of multi-modality
biomedical image control point detection,
registration, and fusion has been successfully
developed. The new algorithm, which consists of the
Adaptive Exploratory Algorithm for the control
point/feature detection and Heuristic Optimization
Algorithm, is reliable and time efficient. The new
approach has been applied on three ophthalmologic
modalities of nonhuman primate eyes - angiogram,
fundus, and oxygen saturation retinal images. It has
achieved an excellent result by giving the
visualization of fundus or oxygen saturation image
with a complete angiogram overlay. By locking the
multi-sensor retinal images in one place, the
algorithm allows ophthalmologists to match the same
eye over time to get a sense of disease progress and
pinpoint surgical tools. The new registration and
fusion algorithm can be easily expanded to the eye,
brain, or body images of human or animals´´. The
target readers are graduate/undergraduate students,
faculty, and research scientists who are interested
in the image registration and fusion algorithms;
ophthalmologists and physicians; image processing
software developers; and whoever wants to learn image
fusion.

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