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Occulusion Enhanced Maximum Intensity Projection Algorithm

Abstract: Occlusion enhanced maximum intensity projection is to solve the problem that#br# maximum intensity projection can?t convey occlusion cue correctly. It consists of two steps:#br# firstly, K-Means clusting algorithm is used to extract structure features from MIP result images#br# automatically; and then it adjusts rendering process adaptively according to structure features.#br# Furthermore, the concept of rendering priority is introduced to avoid important features being#br# occluded badly by non-important features, and an algorithm is provided to set rendering priority of#br# structure feature automatically. Test result of several volume data indicates that OEMIP can#br# enhance occlusion cue significantly, and rendering speed is enough for real-time interaction.#br# Key words: volume visualization; maximum intensity projection; occlusion cue; structure#br# feature   

  • Online:2015-06-30 Published:2015-05-05

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Abstract: Occlusion enhanced maximum intensity projection is to solve the problem that
maximum intensity projection cant convey occlusion cue correctly. It consists of two steps:
firstly, K-Means clusting algorithm is used to extract structure features from MIP result images
automatically; and then it adjusts rendering process adaptively according to structure features.
Furthermore, the concept of rendering priority is introduced to avoid important features being
occluded badly by non-important features, and an algorithm is provided to set rendering priority of
structure feature automatically. Test result of several volume data indicates that OEMIP can
enhance occlusion cue significantly, and rendering speed is enough for real-time interaction.

Key words: volume visualization, maximum intensity projection, occlusion cue, structure
feature