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
J. Ehrhardt
中科院分区:
--
文献类型:
--
作者:
H. Uzunova;S. Schultz;H. Handels;J. Ehrhardt

文献摘要

参考文献

被引文献

相似文献

在开发医学图像应用程序时,通常在验证数据集上评估其准确性,该验证数据集通常与真实的临床数据不同。由于临床数据不包含地面实况注释,因此不可能近似该方法的真实的准确度。在这项工作中,提出了一种基于cGAN的方法来生成逼真的临床数据,保留了拓扑结构,从而保留了验证集的真实情况。在脑MRI的图像配准的例子中,我们强调了该方法的必要性,并表明它可以评估临床数据集的准确性。此外,所生成的图像的拓扑保持和逼真的外观进行评估,并认为是足够的。
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.
多模式的脑肿瘤图像分割基准(Brats)。
DOI: 10.1109/tmi.2014.2377694
发表时间: 2015-10
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