zax130/smilecode

The public code of SMILE LAB

smilecode's Issues

Method of making a data set in.PKL format in a paper.

Hello, first of all, thank you very much for your contribution, which is very useful to me. In addition, I would like to ask you about the method of superimposing the label diagram and the structure diagram to make the.PKL format data set in the paper.It would be nice if you could share the preprocessing data set, thank you very much.

图像尺寸

你好！我想请教以下几个问题：
1.如何裁剪mind101数据集的尺寸大小？另外我在官网似乎没有看到label的注释，预处理数据集的时候seg_norm的标签怎么填写呢？
2.想问一下modeT能否运行160，192，224的图像？
3.运行30epoch的modeT大约需要多久？我跑了几轮感觉时间略久
感谢！

老哥，你好

老哥，能否提供下mindboogle处理好的数据集呀

数据集

Mindboggle数据集如何进行实验

数据集问题

您好，我是一个刚接触医学图像处理的学生，想运行一下您的代码，但是您给的数据集链接里有很多个LPBA，我不确定下载哪一个，您可以详细说明一下应该下载哪一个数据集吗？谢谢！

Issue with Training Phase - Only Achieving 0.2 DSC on Validation Set

Hello,

I've noticed that during the training phase, the Dice Similarity Coefficient (DSC) consistently remains around 0.2. Is this behavior normal for ModeT? I am working with the OASIS dataset, and my Dataloader is consistent with TransMorph, with img_size = (160, 192, 224). Besides these settings, I haven't made any other modifications. To rule out any environment issues due to PyTorch versions, I tested with torch=1.7.0, 1.9.0, 1.10.0, and 1.11.0, but the results were consistently around 0.2. It's worth mentioning that I previously ran TransMorph successfully using version 1.9.0.

Do you have any insights into why ModeT might exhibit this behavior? I would greatly appreciate your guidance in resolving this issue.

Thank you for your time and assistance.

Are there any articles that introduce when to use a velocity field and a displacement field? I can't tell these two apart.

Thank you for your work,are there any articles that introduce when to use a velocity field and a displacement field? I can't tell these two apart.And I don't know when to use velocity field or displacement field.
class VecInt(nn.Module):

def __init__(self, inshape, nsteps=7):
    super().__init__()

    assert nsteps >= 0, 'nsteps should be >= 0, found: %d' % nsteps
    self.nsteps = nsteps
    self.scale = 1.0 / (2 ** self.nsteps)
    self.transformer = SpatialTransformer(inshape)

def forward(self, vec):
    vec = vec * self.scale
    for _ in range(self.nsteps):
        vec = vec + self.transformer(vec, vec)
    return vec

Question about 'dice_val_VOI' in utils.py for LPBA40 dataset

def dice_val_VOI(y_pred, y_true):
    VOI_lbls = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
                12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
                24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
                48, 49, 50, 51, 52, 53, 54]

    pred = y_pred.detach().cpu().numpy()[0, 0, ...]
    true = y_true.detach().cpu().numpy()[0, 0, ...]
    DSCs = np.zeros((len(VOI_lbls), 1))
    idx = 0
    for i in VOI_lbls:
        pred_i = pred == i
        true_i = true == i
        intersection = pred_i * true_i
        intersection = np.sum(intersection)
        union = np.sum(pred_i) + np.sum(true_i)
        dsc = (2.*intersection) / (union + 1e-5)
        DSCs[idx] =dsc
        idx += 1
    return np.mean(DSCs)

Hello, I noticed that the "dice_val_VOI" in your code under the "utils.py" file doesn't seem to correspond to the labels of the LPBA40 dataset. Where does the data in this list come from, and what is it used for? I would appreciate your guidance.

爹！您好

爹，能问下那个形变场可视化用的啥工具吗？麻烦爹！

关于mindboggle数据集

您好，我在您给的链接中找到了多个文件夹的数据，请问是用这个FreeSurfer_output文件夹里面的数据吗？