File size: 3,263 Bytes
a539579 | 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 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | # Structured crowdsourcing enables convolutional segmentation of histology images
This repo contains the necessary information and download instructions to download the dataset associated with the paper:
***_Amgad M, Elfandy H, ..., Gutman DA, Cooper LAD. Structured crowdsourcing enables convolutional segmentation of histology images. Bioinformatics. 2019. doi: 10.1093/bioinformatics/btz083_***
This data can be visualized in a public instance of the DSA at https://goo.gl/cNM4EL.
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## Usage
- Each mask is a .png image, where pixel values encode region class membership. The meaning of ground truth encoded can be found at the file `./meta/gtruth_codes.tsv`.
- The name of each mask encodes all necessary information to extract the corresponding RGB images from TCGA slides. For convenience, RGBs are also downloaded using the code used here.
- **[CRITICAL] -** Please be aware that zero pixels represent regions outside the region of interest (“don’t care” class) and should be assigned zero-weight during model training; they do **NOT** represent an “other” class.
- The RGBs and corresponding masks will be at the set `MPP` resolution. If `MPP` was set to `None`, then they
would be at `MAG` magnification. If both are set to `None`, then they will be at the base (scan) magnification.
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## Download (Single link - convenient)
You can use [this link](https://drive.google.com/drive/folders/1zqbdkQF8i5cEmZOGmbdQm-EP8dRYtvss?usp=sharing) to download the dataset at 0.25 MPP resolution.
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## Download (command line - flexible)
Use this to download all elements of the dataset using the command line.
This script will download any or all of the following:
- annotation JSON files (coordinates)
- masks
- RGB images
Steps are as follows:
**Step 0: Clone this repo**
```bash
$ git clone https://github.com/CancerDataScience/CrowdsourcingDataset-Amgadetal2019
$ cd CrowdsourcingDataset-Amgadetal2019
```
**Step 1: Instal requirements**
`pip install girder_client girder-client pillow numpy scikit-image imageio`
**Step 2 (optional): Edit `configs.py`**
If you like, you may edit various download configurations. Of note:
- `SAVEPATH` - where everything will be saved
- `MPP` - microns per pixel for RGBs and masks (preferred, default is 0.25)
- `MAG` - magnification (overridden by `MPP` if `MPP` is set. default is None)
- `PIPELINE` - what elements to download?
**Step 3: Run the download script**
`python download_crowdsource_dataset.py`
The script will create the following sub-directories in `SAVEPATH`:
|_ annotations : where JSON annotations will be saves for each slide
|_ masks : where the ground truth masks to use for training and validation are saved
|_ images: where RGB images corresponding to masks are saved
|_ wsis (legacy) : Ignore this. No longer supported.
|_ logs : in case anythign goes wrong
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## Licensing
This dataset is licensed under a [CC BY 4.0 license](https://creativecommons.org/licenses/by/4.0/).
Please cite our paper if you use the data.
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