Open yoonguusong opened 3 years ago
Our preprocessing stage also resizes all image crops to the same resolution. The spacing information will be changed, but the resulting deformation field can be transformed back.
I have another questions as well.
If you see the demo.py, there is "img_fixed, reader_fixed = preprocess_dcm(args.fixed)" what preprocessing will be done if you run this code?
which data format did you applied? nii? mnc? dcm?
I'm trying to follow your method but hard to understand it. Thank you for your kindness
The demo assumes the inputs being of DICOM series. The preprocessing stage first finds a rough bounding box of the liver area (using a threshold-based algorithm), crop the area accordingly and resize to 128^3, and then normalizes the intensity.
我想请问一下 当我用您的网络去训练一组别的数据集 他是192192192的 怎么进行更改呢
I have a question to match different 3D medical dataset into same dataset size without losing or tilting medical information. I am trying to match medical image using nib.Nifti1Image(image_resized, affine=None), but this seems changing medical data information.