( en | de | ru )

 

Disambiguation of "Ye, Xujiong"

Author of the publication

copydeleteadd this publication to your clipboard
Segmenting Atrial Fibrosis from Late Gadolinium-Enhanced Cardiac MRI by Deep-Learned Features with Stacked Sparse Auto-Encoders.

, , , , , , , , , , and . MIUA, volume 723 of Communications in Computer and Information Science, page 195-206. Springer, (2017)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Ying Ye

Ye Chen

Fei Ye

Ye Hu

Zhenyu Ye

 

Other publications of authors with the same name

Automated Polyp Segmentation in Colonoscopy Frames Using Fully Convolutional Neural Network and Textons., , and . MIUA, volume 723 of Communications in Computer and Information Science, page 707-717. Springer, (2017)MIXR: A Standard Architecture for Medical Image Analysis in Augmented and Mixed Reality., , and . AIVR, page 252-257. IEEE, (2020)Shape-Based CT Lung Nodule Segmentation Using Five-Dimensional Mean Shift Clustering and Mem with Shape Information., , , , and . ISBI, page 482-485. IEEE, (2009)Pushing the Limits of Cell Segmentation Models for Imaging Mass Cytometry., , , and . ISBI, page 1-5. IEEE, (2024)Segmentation of Left Ventricle in 2D Echocardiography Using Deep Learning., , , , , and . MIUA, volume 1065 of Communications in Computer and Information Science, page 497-504. Springer, (2019)Weakly supervised pre-training for brain tumor segmentation using principal axis measurements of tumor burden., , , and . Frontiers Comput. Sci., (2024)Zero-dimensional biomarker based medical action recognition: towards more explainable AI in healthcare., , , and . ICBRA, page 143-148. ACM, (2023)A fully automatic deep learning method for atrial scarring segmentation from late gadolinium-enhanced MRI images., , , , , , , , , and 1 other author(s). ISBI, page 844-848. IEEE, (2017)DR-Unet104 for Multimodal MRI Brain Tumor Segmentation., , , and . BrainLes@MICCAI (2), volume 12659 of Lecture Notes in Computer Science, page 410-419. Springer, (2020)Multimodal MRI brain tumor segmentation using random forests with features learned from fully convolutional neural network., , , , and . CoRR, (2017)