Evaluation of Image Processing Methods for Clinical Applications - Mimicking Clinical Data Using Conditional GANs
Evaluation of Image Processing Methods for Clinical Applications - Mimicking Clinical Data Using Conditional GANs
复制标题
临床应用图像处理方法的评估 - 使用条件 GAN 模拟临床数据
DOI:
10.1007/978-3-658-25326-4_5
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
J. Ehrhardt
中科院分区:
文献类型:
--
作者:
H. Uzunova;S. Schultz;H. Handels;J. Ehrhardt
While developing medical image applications, their accuracy is usually evaluated on a validation dataset, that generally differs from the real clinical data. Since clinical data does not contain ground truth annotations, it is impossible to approximate the real accuracy of the method. In this work, a cGAN-based method to generate realistically looking clinical data preserving the topology and thus ground truth of the validation set is presented. On the example of image registration of brain MRIs, we emphasize the necessity for the method and show that it enables evaluation of the accuracy on a clinical dataset. Furthermore, the topology preserving and realistic appearance of the generated images are evaluated and considered to be sufficient.
影响因子:
10.6
作者:
Menze BH;Jakab A;Bauer S;Kalpathy-Cramer J;Farahani K;Kirby J;Burren Y;Porz N;Slotboom J;Wiest R;Lanczi L;Gerstner E;Weber MA;Arbel T;Avants BB;Ayache N;Buendia P;Collins DL;Cordier N;Corso JJ;Criminisi A;Das T;Delingette H;Demiralp Ç;Durst CR;Dojat M;Doyle S;Festa J;Forbes F;Geremia E;Glocker B;Golland P;Guo X;Hamamci A;Iftekharuddin KM;Jena R;John NM;Konukoglu E;Lashkari D;Mariz JA;Meier R;Pereira S;Precup D;Price SJ;Raviv TR;Reza SM;Ryan M;Sarikaya D;Schwartz L;Shin HC;Shotton J;Silva CA;Sousa N;Subbanna NK;Szekely G;Taylor TJ;Thomas OM;Tustison NJ;Unal G;Vasseur F;Wintermark M;Ye DH;Zhao L;Zhao B;Zikic D;Prastawa M;Reyes M;Van Leemput K
通讯作者:
Van Leemput K