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@@ -29,4 +29,58 @@ license: apache-2.0
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  task_categories:
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  - image-classification
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  - feature-extraction
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  task_categories:
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  - image-classification
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  - feature-extraction
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+ ---
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+
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+ ## Dataset Structure
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+ This dataset contains vision data for chest X-ray pathology identification.
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+
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+ ### Data Fields
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+ - **image**: The PIL image of the chest X-ray. These images are size (224,224) by default.
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+ - **pathols**: A binary-valued (14)-shaped array that indicates whether each of the 14 pathologies is present.
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+ - **structs**: A binary-valued array of shapes (14,224,224) that gives the segmentation for each of the 14 anatomical structures.
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+
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+ The 14 pathologies are:
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+
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+ 0. Atelectasis
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+ 1. Cardiomegaly
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+ 2. Consolidation
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+ 3. Edema
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+ 4. Effusion
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+ 5. Emphysema
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+ 6. Fibrosis
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+ 7. Hernia
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+ 8. Infiltration
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+ 9. Mass
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+ 10. Nodule
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+ 11. Pleural Thickening
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+ 12. Pneumonia
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+ 13. Pneumothorax
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+
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+ The 14 anatomical structures are:
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+
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+ 0. Left Clavicle
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+ 1. Right Clavicle
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+ 2. Left Scapula
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+ 3. Right Scapula
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+ 4. Left Lung
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+ 5. Right Lung
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+ 6. Left Hilus Pulmonis
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+ 7. Right Hilus Pulmonis
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+ 8. Heart
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+ 9. Aorta
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+ 10. Facies Diaphragmatica
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+ 11. Mediastinum
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+ 12. Weasand
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+ 13. Spine
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+
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+ ### Data Splits
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+ - **train**: 23094 samples
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+ - **test**: 5774 samples
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+
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+
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+ ## Usage
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+ ```
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+ from datasets import load_dataset
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+ train_dataset = load_dataset("BrachioLab/chestx", split="train")
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+ test_dataset = load_dataset("BrachioLab/chestx", split="test")
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+ ```