Acute ischemic stroke dataset

Related tags

Deep Learning AISD
Overview

AISD

Acute ischemic stroke dataset contains 397 Non-Contrast-enhanced CT (NCCT) scans of acute ischemic stroke with the interval from symptom onset to CT less than 24 hours. The patients underwent diffusion-weighted MRI (DWI) within 24 hours after taking the CT. The slice thickness of NCCT is 5mm. 345 scans are used to train and validate the model, and the remaining 52 scans are used for testing. Ischemic lesions are manually contoured on NCCT by a doctor using MRI scans as the reference standard. Then a senior doctor double-reviews the labels.

  1. Download the image data (image.zip) [Baidu YUN] with the password "aisd".
  2. Download the mask data (mask.zip) [Baidu YUN] with the password "aisd".

Samples

Citation

If you use this code, please cite the following paper(s):

@inproceedings{liang2021SymmetryEnhancedAN,
	title={Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images},    
	author={Kongming Liang, Kai Han, Xiuli Li, Xiaoqing Cheng, Yiming Li, Yizhou Wang, and Yizhou Yu},    
	booktitle={MICCAI},    
	year={2021}    
}

License

This dataset is made freely available to academic and non-academic entities for non-commercial purposes such as academic research, teaching, scientific publications, or personal experimentation.

Comments
  • No Download from the US possible

    No Download from the US possible

    Hi Kongming,

    That for making your dataset public! I cannot download your dataset from the US. Baidu does not allow an oversea account and downloading without an account did not work. Would it be possible to download your dataset from somewhere else?

    Thank you!

    Best, Sophie

    opened by SophieOstmeier 3
  • Train test split

    Train test split

    Hi Griffin,

    Thanks for sharing the data. I was wondering whichs patients IDs correspond to the training data, and which to the test data. Could you provide me with a list?

    Thanks a lot!

    opened by lauravanpoppel 2
  • Dicom or Nifti files

    Dicom or Nifti files

    Hi,

    The files are PNG format. Could you share the Dicoms / Nifti images? Or, could you elaborate on the preprocessing? All HU are now converted to PNG (0, 255). What is the inverse transformation needed to get the correct HU values?

    Thanks!

    opened by lucasdevries 2
  • About symmetry based alignment network and the data

    About symmetry based alignment network and the data

    Hi Griffin, 非常感谢你和团队将数据无私地分享给大伙。我看了你的文章，有两个问题想请教下：

    1. 文章Result 部分有提到 symmetry based alignment network 速度极快（0.46s per patient on average). 这是基于整个3D volume的结果，还是某一层？是否可以提供个demo试用下效果？
    2. 标注部分，参照的标准时24小时内的核磁dwi。是否有考虑过，dwi上的高亮信号不一定是全是梗死的因素（我看到你们的网络结果，dice已经最好了，但是可能离实际应用还是有些距离，所以怀疑标注这块是否可能存在误差）。
    opened by jiangliMED 1
  • How do you compute your Dice value in the paper?

    How do you compute your Dice value in the paper?

    Hi, @GriffinLiang, your work is quite interesting! But I am confused about how you compute the Dice value. I try some simple baselines but the results are quite different from yours. Could you give more details about how you compute the metrics you reported in your paper?

    Thanks!

    opened by nihaomiao 0
  • Can you give the clinical information sheet including patient ID and ASPECTS?

    Can you give the clinical information sheet including patient ID and ASPECTS?

    Hi Griffin, Thank you very much for sharing this valuable dataset. I would like to use your dataset for automated ASPECTS scoring. Can you give the clinical information sheet including patient ID , ASPECTS, age, gender, onset-to-CT time and CT-to-MRI time? Thanks

    opened by hulinkuang 1
  • Slice thickness

    Slice thickness

    Thank you for releasing the data from your paper. I noticed the number of slices ranges from 11 to 63 among the cases. Is the slice thickness 5mm for every case?

    opened by rahulghosh2 1
  • Mask values meaning

    Mask values meaning

    First of all, thank you very much for releasing the data. I've noticed that there're multiple labels (1-5) in the mask.

    What is the meaning of each labels?

    opened by charleswg 5
Owner
Kongming Liang
Kongming Liang
GitHub
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