论文信息 - Automatic Segmentation of Lumbar Spine MRI Using Ensemble of 2D Algorithms

Automatic Segmentation of Lumbar Spine MRI Using Ensemble of 2D Algorithms

MRI is considered the gold standard in soft tissue diagnostic of the lumbar spine. Number of protocols and modalities are used – from one hand 2D sagittal, 2D angulated axial, 2D consecutive axial and 3D image types; from the other hand different sequences and contrasts are used: T1w, T2w; fat suppression, water suppression etc. Images of different modalities are not always aligned. Resolutions and field of view also vary. SNR is also different for different MRI equipment. So the goal should be to create an algorithm that covers great variety of imaging techniques.

A. Asenov | Nedelcho Georgiev | A. Asenov | N. Georgiev

[1] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[2] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.

[3] Yoshua Bengio,et al. Reading checks with multilayer graph transformer networks , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[4] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[5] Hao Chen,et al. 3D multi‐scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi‐modality MR Images , 2018, Medical Image Anal..

[6] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.

[7] Guoyan Zheng,et al. 3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification , 2014, MLMI.