ISpace: Interactive volume data classification techniques using independent component analysis

被引：12
|
作者：
Takanashi, I
Lum, EB
Ma, KL
Muraki, S
机构：
来源：
10TH PACIFIC CONFERENCE ON COMPUTER GRAPHICS AND APPLICATIONS, PROCEEDINGS | 2002年
关键词：
histogram; image processing; independent component analysis; medical imaging; multivariate data analysis; multimodality data; scientific visualization; segmentation; volume rendering;
D O I：
10.1109/PCCGA.2002.1167880
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
This paper introduces an interactive classification technique for volume data, called ISpace, which uses Independent Component Analysis (ICA) and a multidimensional histogram of the volume data in a transformed space. Essentially, classification in the volume domain becomes equivalent to interactive clipping in the ICA space, which as demonstrated using several examples is more intuitive and direct for the user to classify data. The result is an opacity transfer function defined for rendering multivariate scalar volume data.
引用
收藏
页码：366 / 374
页数：9
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