PaddleSeg/contrib/MedicalSeg/configs/mri_spine_seg

• MRISpineSeg
• • Performance
  • • Vnet
    • Unet

MRISpineSeg

There are 172 training data in the preliminary competition, including MR images and mask labels, 20 test data in the preliminary competition and 23 test data in the second round competition. The labels of the preliminary competition testset and the second round competition testset are not published.

Performance

Vnet

Milletari, Fausto, Nassir Navab, and Seyed-Ahmad Ahmadi. "V-net: Fully convolutional neural networks for volumetric medical image segmentation." In 2016 fourth international conference on 3D vision (3DV), pp. 565-571. IEEE, 2016.

Backbone	Resolution	lr	Training Iters	Dice(20 classes)	Dice(16 classes*)	Links
-	512x512x12	0.1	15000	74.41%	88.17%	model | log | vdl
-	512x512x12	0.5	15000	74.69%	89.14%	model | log | vdl

16 classes*: 16 classes removed T9, T10, T9/T10 and T10/T11 from calculating the mean Dice compared from the 20 classes.

Unet

Çiçek, Özgün, Ahmed Abdulkadir, Soeren S. Lienkamp, Thomas Brox, and Olaf Ronneberger. "3D U-Net: learning dense volumetric segmentation from sparse annotation." In International conference on medical image computing and computer-assisted intervention, pp. 424-432. Springer, Cham, 2016.

Backbone	Resolution	lr	Training Iters	Dice	Links

To be continue.