Evaluating segmentation algorithms for diffusion-weighted MR images: a task-based approach.
Evaluating segmentation algorithms for diffusion-weighted MR images: a task-based approach.
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评估扩散加权 MR 图像的分割算法:基于任务的方法。
DOI:
10.1117/12.845515
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发表时间:
2010
期刊:
影响因子:
--
通讯作者:
Stopeck,AlisonT
中科院分区:
文献类型:
--
作者:
Jha,AbhinavK;Kupinski,MatthewA;Rodríguez,JeffreyJ;Stephen,RenuM;Stopeck,AlisonT
Apparent Diffusion Coefficient (ADC) of lesions obtained from Diffusion Weighted Magnetic Resonance Imaging is an emerging biomarker for evaluating anti-cancer therapy response. To compute the lesion's ADC, accurate lesion segmentation must be performed. To quantitatively compare these lesion segmentation algorithms, standard methods are used currently. However, the end task from these images is accurate ADC estimation, and these standard methods don't evaluate the segmentation algorithms on this task-based measure. Moreover, standard methods rely on the highly unlikely scenario of there being perfectly manually segmented lesions. In this paper, we present two methods for quantitatively comparing segmentation algorithms on the above task-based measure; the first method compares them given good manual segmentations from a radiologist, the second compares them even in absence of good manual segmentations.
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影响因子:
8
作者:
Kushtai,G;Barzilay,J;Feldman,M;Eisenbach,L
通讯作者:
Eisenbach,L
DOI:
--
发表时间:
1985
期刊:
Journal of the National Cancer Institute
影响因子:
--
作者:
Eisenbach,L;Segal,S;Feldman,M
通讯作者:
Feldman,M
DOI:
--
发表时间:
1982
期刊:
影响因子:
--
作者:
S. Katzav;P. Baetselier;B. Tartakovsky;S. Segal;M. Feldman
通讯作者:
M. Feldman
DOI:
--
发表时间:
1985
期刊:
Journal of the National Cancer Institute
影响因子:
--
作者:
Eisenbach,L;Segal,S;Feldman,M
通讯作者:
Feldman,M
影响因子:
64.8
作者:
NAU, MM;BROOKS, BJ;MINNA, JD
通讯作者:
MINNA, JD