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Influence of kernel paradigms, attribute numbers or data filtering on the performance of SVM in pred
[会议论文] 作者：XinZhang,Lin-FengYan,Hai-YanNan,YangYang,Yu-ChuanHu,JinZhang,YuHan,Guang-BinCui,WenWang,
来源：中华放射学学术大会2016、中华医学会第23次全国放射学学术大会暨中华医学会第24次全国影像技术学术大会 年份：2016
Purpose: Support vector machine (SVM) model learning is commonly used in tumor prognosis evaluation for prostate cancer, breast cancer, glioma, etc. However, the influence of kernel paradigms, attribu...
Comparison of conventional or tumor geography based parameters from DCE-MRI,3D-ASL and multi-b diffu
[会议论文] 作者：LinfengYan,XinZhang,YangYang,YuHan,JinZhang,YingYu,Yu-ChuanHu,Hai-YanNan,Zhi-ChengLiu,Guang-BinCui,WenWang,
来源：中华放射学学术大会2016、中华医学会第23次全国放射学学术大会暨中华医学会第24次全国影像技术学术大会 年份：2016
Purpose: Multimodal MRI especially dynamic contrast enhancement MRI(DCE-MRI),diffusion weight imaging MRI(DWI-MRI)and 3-D arterial spin labeling(3D-ASL)images demonstrate superiority over conventional...
Optimized automatic classification of IDH1 based on comprehensive tumor histogram and texture featur
[会议论文] 作者：WenWang,Lin-FengYan,XinZhang,YangYang,YuHan,JinZhang,YingYu,Zhi-ChengLiu,Hai-YanNan,Yu-ChuanHu,WenWang,
来源：中华放射学学术大会2016、中华医学会第23次全国放射学学术大会暨中华医学会第24次全国影像技术学术大会 年份：2016
Purpose: To perform data mining of the multimodal diagnostic MRI images with support vector machine(SVM)model learning based on the combination of image textures and histograms and to optimize the com...
Optimizingmathematicmodelandgrayleveltoimprovetheclassificationaccuracyoftumorgradein
[会议论文] 作者：YangYang,Lin-FengYan,Hai-yanNan,XinZhang,Yu-ChuanHu,YuHan,JinZhang,YingYu,Zhi-ChengLiu,Ying-ZhiSun,
来源：中华放射学学术大会2016、中华医学会第23次全国放射学学术大会暨中华医学会第24次全国影像技术学术大会 年份：2016
Purpose:TextfeaturesofmedicalimagesareimportantdataformatforSupportvectormachine(SVM)learninginpreoperative tumorgradingforprostatecancer,breastcancer,glioma,ect....
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