Gaussian modelling for operator-independent and threshold-free volumetric segmentation of phase sensitive inversion recovery late gadolinium enhanced images

Stefan K Piechnik; Erica DallArmellina; Vanessa M Ferreira; Matthew D Robson

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Gaussian modelling for operator-independent and threshold-free volumetric segmentation of phase sensitive inversion recovery late gadolinium enhanced images

机译：高斯建模，用于相敏感反演恢复late增强影像的独立于运算符的无阈值体积分割

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来源
《Journal of cardiovascular magnetic resonance :》 |2011年第1期|共页
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Stefan K Piechnik; Erica DallArmellina; Vanessa M Ferreira; Matthew D Robson;
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中图分类心脏、血管（循环系）疾病;
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1. New automatic algorithm for segmentation of myocardial scar in both inversion recovery and phase sensitive inversion recovery late gadolinium enhancement: validation against TTC and in multi-center, multi-vendor patient data [J] . Jane Tufvesson, Robert Jablonowski, Henrik Engblom, Journal of cardiovascular magnetic resonance : . 2016,第S1期

机译：在automatic恢复和相敏反转恢复中late分割后期使用的新型心肌疤痕自动分割算法：针对TTC和多中心，多供应商患者数据的验证
2. New automatic algorithm for segmentation of myocardial scar in both inversion recovery and phase sensitive inversion recovery late gadolinium enhancement: validation against TTC and in multi-center, multi-vendor patient data [J] . Jane Tufvesson, Robert Jablonowski, Henrik Engblom, Journal of cardiovascular magnetic resonance : . 2016,第S1期

机译：在automatic恢复和相敏反转恢复中late分割后期使用的新型心肌疤痕自动分割算法：针对TTC和多中心，多供应商患者数据的验证
3. Free-breathing 3D phase-sensitive inversion recovery late gadolinium enhancement at 3.0 Tesla: reliability and image quality in ischemic and non-ischemic cardiomyopathy in comparison with multiple breath-hold 3D imaging [J] . Maurice Bizino, Jacob Amersfoort, Qian Tao, Journal of cardiovascular magnetic resonance : . 2015,第Suppla1期

机译：自由呼吸的3D相敏反转恢复，在3.0特斯拉时后期enhancement增强：与多次屏气3D成像相比，缺血性和非缺血性心肌病的可靠性和图像质量
4. Fully Automated Segmentation of Left Ventricular Myocardium from 3D Late Gadolinium Enhancement Magnetic Resonance Images Using a U-Net Convolutional Neural Network-Based Model [C] . Fatemeh Zabihollahy, James A. White, Eranga Ukwatta SPIE Conference on Computer-Aided Diagnosis . 2019

机译：使用U-Net卷积神经网络的模型，从3D晚期钆增强磁共振图像全自动分割左心室心肌。
5. Enhancing the potential of the conventional Gaussian mixture model for segmentation: From images to videos. [D] . Mukherjee, Dibyendu. 2014

机译：增强传统高斯混合模型进行细分的潜力：从图像到视频。
6. Gaussian modelling for operator-independent and threshold-free volumetric segmentation of phase sensitive inversion recovery late gadolinium enhanced images [O] . Stefan K Piechnik, Erica DallArmellina, Vanessa M Ferreira, 2011

机译：高斯建模用于相敏感反演恢复后期ado增强图像的独立于操作者且无阈值的体积分割
7. Gaussian modelling for operator-independent and threshold-free volumetric segmentation of phase sensitive inversion recovery late gadolinium enhanced images [O] . Stefan K Piechnik, Erica DallArmellina, Vanessa M Ferreira, 2011

机译：高斯建模，用于相敏感反演恢复后期ado增强图像的独立于操作者且无阈值的体积分割

Gaussian modelling for operator-independent and threshold-free volumetric segmentation of phase sensitive inversion recovery late gadolinium enhanced images

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