This brain tumor dataset containing 3064 T1-weighted contrast-inhanced images from 233 patients with three kinds of brain tumor: meningioma (708 slices), glioma (1426 slices), and pituitary tumor (930 slices). The images are 512x512 pixels.
Original dataset was published here: https://doi.org/10.6084/m9.figshare.1512427.v5
This dataset utilises the converted version of the original dataset. I host the zip file on my own server to make it easier to download, and made a TFDS dataset from it, which is this repo.
Note that I have not yet implemented the test scripts; please contribute if you can.
This brain tumor dataset containing 3064 T1-weighted contrast-inhanced images from 233 patients with three kinds of brain tumor: meningioma (708 slices), glioma (1426 slices), and pituitary tumor (930 slices). Due to the file size limit of repository, we split the whole dataset into 4 subsets, and achive them in 4 .zip files with each .zip file containing 766 slices.The 5-fold cross-validation indices are also provided.
This data is organized in matlab data format (.mat file). Each file stores a struct containing the following fields for an image:
cjdata.label: 1 for meningioma, 2 for glioma, 3 for pituitary tumor cjdata.PID: patient ID cjdata.image: image data cjdata.tumorBorder: a vector storing the coordinates of discrete points on tumor border. For example, [x1, y1, x2, y2,...] in which x1, y1 are planar coordinates on tumor border. It was generated by manually delineating the tumor border. So we can use it to generate binary image of tumor mask. cjdata.tumorMask: a binary image with 1s indicating tumor region
This data was used in the following paper:
- Cheng, Jun, et al. "Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition." PloS one 10.10 (2015).
- Cheng, Jun, et al. "Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation." PloS one 11.6 (2016). Matlab source codes are available on github https://github.com/chengjun583/brainTumorRetrieval
Jun Cheng School of Biomedical Engineering Southern Medical University, Guangzhou, China Email: chengjun583@qq.com
For example, on Google Colab:
!wget https://github.com/BirkhoffLee/dataset-figshare/archive/refs/heads/main.zip
!unzip main.zip
!rm main.zip
!mv dataset-figshare-main brain_tumor_figshare
!tfds build brain_tumor_figshare
After it's built, you can use it as a normal TFDS dataset:
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import tensorflow_datasets as tfds
ds, info = tfds.load('brain_tumor_figshare', split='all', with_info=True)
tfds.as_dataframe(ds.take(4), info) # This takes 4 data and plots themThe original dataset is licensed under the CC BY 4.0 License. If you use this dataset, please cite the original authors.