Abstract：
:Image interpolation is an important operation that is widely used in medical imaging, image processing, and computer graphics. A variety of interpolation methods are available in the literature. However, their systematic evaluation is lacking. In a previous paper, we presented a framework for the task-independent comparison of interpolation methods based on certain image-derived figures of merit using a variety of medical image data pertaining to different parts of the human body taken from different modalities. In this work, we present an objective task-specific framework for evaluating interpolation techniques. The task considered is how the interpolation methods influence the accuracy of quantification of the total volume of lesions in the brain of multiple sclerosis (MS) patients. Sixty lesion-detection experiments coming from ten patient studies, two subsampling techniques and the original data, and three interpolation methods are carried out, along with a statistical analysis of the results.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Grevera GJ,Udupa JK,Miki Ydoi
10.1109/42.759116subject
Has Abstractpub_date
1999-02-01 00:00:00pages
137-43issue
2eissn
0278-0062issn
1558-254Xjournal_volume
18pub_type
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journal_title：IEEE transactions on medical imaging
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pub_type： 信件
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pub_type： 杂志文章
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doi：10.1109/TMI.2006.883453
更新日期：2006-11-01 00:00:00
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更新日期：2003-03-01 00:00:00
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pub_type： 杂志文章
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