| --- |
| license: cc0-1.0 |
| task_categories: |
| - image-classification |
| tags: |
| - medical |
| - chest-x-ray |
| - multi-label |
| - radiology |
| pretty_name: NIH ChestX-ray14 (Preprocessed) |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # NIH ChestX-ray14 — Preprocessed Dataset |
|
|
| ## Dataset Description |
|
|
| Preprocessed version of the NIH ChestX-ray14 dataset for multi-label thoracic disease classification. |
|
|
| ### Source |
| - **Original Dataset:** [NIH ChestX-ray14](https://nihcc.app.box.com/v/ChestXray-NIHCC) |
| - **Institution:** NIH Clinical Center |
| - **License:** CC0 1.0 (Public Domain) |
|
|
| ### Citation |
|
|
| ```bibtex |
| @inproceedings{wang2017chestx, |
| title={ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases}, |
| author={Wang, Xiaosong and Peng, Yifan and Lu, Le and Lu, Zhiyong and Bagheri, Mohammadhadi and Summers, Ronald M}, |
| booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, |
| pages={2097--2106}, |
| year={2017} |
| } |
| ``` |
|
|
| ## Preprocessing Pipeline |
|
|
| ### 1. Quality Filtering |
| Images were filtered based on pixel intensity statistics from the original 112,120 images: |
| - **Too dark (mean < 50):** 61 images removed, 28 manually cropped (black border removal) and retained |
| - **Too bright (mean > 195):** 52 images removed, 2 manually cropped (white border removal) and retained |
| - **Low contrast (std < 25 after CLAHE):** 28 images removed, 1 retained (00004480_000.png) |
| - **Total removed:** 141 images |
| - **Total retained:** 111,979 images |
| |
| ### 2. Image Processing (applied to all retained images) |
| 1. **CLAHE** (Contrast Limited Adaptive Histogram Equalization): clipLimit=2.0, tileGridSize=(8,8) |
| 2. **Resize:** 224×224 pixels, Bilinear interpolation |
| 3. **Channel:** Grayscale → 3-channel RGB (channel replication) |
| 4. **Format:** PNG |
| |
| ### 3. Normalization |
| Not applied at save time. Apply ImageNet normalization at DataLoader time: |
| - mean = [0.485, 0.456, 0.406] |
| - std = [0.229, 0.224, 0.225] |
| |
| ### 4. Train/Test Split |
| - **Method:** Patient ID-based GroupShuffleSplit (85/15) |
| - **Train:** 96,359 images (26,152 patients) |
| - **Test:** 15,620 images (4,616 patients) |
| - **Patient overlap:** 0 (verified) |
| |
| ### 5. Cross-Validation |
| - **Method:** 5-Fold GroupKFold (Patient-wise) on train set |
| - **Fold column** included in `train.csv` (values 0–4) |
| - **Fold-to-fold patient overlap:** 0 (verified) |
| |
| ### 6. Multi-hot Encoding |
| 14 diseases encoded in alphabetical order: |
| |
| | Index | Disease | |
| |-------|---------| |
| | 0 | Atelectasis | |
| | 1 | Cardiomegaly | |
| | 2 | Consolidation | |
| | 3 | Edema | |
| | 4 | Effusion | |
| | 5 | Emphysema | |
| | 6 | Fibrosis | |
| | 7 | Hernia | |
| | 8 | Infiltration | |
| | 9 | Mass | |
| | 10 | Nodule | |
| | 11 | Pleural_Thickening | |
| | 12 | Pneumonia | |
| | 13 | Pneumothorax | |
|
|
| "No Finding" → all zeros `[0,0,0,0,0,0,0,0,0,0,0,0,0,0]` |
|
|
| ## Directory Structure |
|
|
| ``` |
| processed/ |
| ├── README.md |
| ├── available/ |
| │ ├── images/ # 111,979 preprocessed images (224×224×3 PNG) |
| │ ├── data.csv # Full metadata + multi-hot encoding |
| │ ├── train.csv # Train split (96,359 rows, includes fold column) |
| │ └── test.csv # Test split (15,620 rows) |
| └── unavailable/ |
| ├── images/ # 141 filtered-out original images |
| └── data.csv # Metadata for filtered images |
| ``` |
|
|
| ## CSV Columns |
|
|
| | Column | Description | |
| |--------|-------------| |
| | Image Index | Filename (e.g., `00000001_000.png`) | |
| | Finding Labels | Pipe-separated labels (e.g., `Atelectasis\|Effusion`) | |
| | Follow-up # | Follow-up visit number | |
| | Patient ID | Unique patient identifier | |
| | Patient Age | Age in years | |
| | Patient Gender | M or F | |
| | View Position | PA or AP | |
| | OriginalImage[Width,Height] | Original image dimensions | |
| | OriginalImagePixelSpacing[x,y] | Pixel spacing | |
| | Atelectasis ... Pneumothorax | Multi-hot encoded disease columns (0 or 1) | |
| | fold | (train.csv only) Cross-validation fold index (0–4) | |
|
|
