ISpace: Interactive Volume Data Classification Techniques Using Independent Component Analysis

Autor:	Takanashi, Ikuko, Lum, Eric, Murakin, Shigeru, Ma, Kwan-Liu
Jazyk:	angličtina
Rok vydání:	2002
Předmět:	ComputingMethodologies_PATTERNRECOGNITION Engineering Histogram image processing independent component analysis medical imaging multivariate data analysis multimodality data scientific visualization segmentation volume rendering
Zdroj:	Takanashi, Ikuko; Lum, Eric; Murakin, Shigeru; & Ma, Kwan-Liu. (2002). ISpace: Interactive Volume Data Classification Techniques Using Independent Component Analysis. 10th Pacific Conference Graphics and Applications (PG'02). UC Davis: Institute for Data Analysis and Visualization. Retrieved from: http://www.escholarship.org/uc/item/2fb2m2fj
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=od_______325::a1b143d05d5dda0866be1fb936e40d6b http://www.escholarship.org/uc/item/2fb2m2fj Zobrazit plný text záznamu