Datasets:
Formats:
parquet
Sub-tasks:
multi-input-text-classification
Languages:
English
Size:
100K - 1M
License:
Dataset Viewer
Image Index
stringlengths 16
16
| Texts
stringlengths 84
210
| View Position
stringclasses 2
values | Image Features
sequencelengths 512
512
| Text Features
sequencelengths 512
512
| Atelectasis
int32 0
1
| Cardiomegaly
int32 0
1
| Effusion
int32 0
1
| Infiltration
int32 0
1
| Mass
int32 0
1
| Nodule
int32 0
1
| Pneumonia
int32 0
1
| Pneumothorax
int32 0
1
| Consolidation
int32 0
1
| Edema
int32 0
1
| Emphysema
int32 0
1
| Fibrosis
int32 0
1
| Hernia
int32 0
1
| Pleural_Thickening
int32 0
1
| No_Finding
int32 0
1
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
00000001_000.png | This photo of a chest x-ray shows a Cardiomegaly finding. The image is taken from a PA view. | PA | [
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00000001_001.png | This photo of a chest x-ray shows multiple findings including Cardiomegaly and Emphysema. The image is taken from a PA view. | PA | [
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00000001_002.png | This photo of a chest x-ray shows multiple findings including Cardiomegaly and Effusion. The image is taken from a PA view. | PA | [
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00000003_001.png | This photo of a chest x-ray shows a Hernia finding. The image is taken from a PA view. | PA | [
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00000003_002.png | This photo of a chest x-ray shows a Hernia finding. The image is taken from a PA view. | PA | [
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00000003_003.png | This photo of a chest x-ray shows multiple findings including Hernia and Infiltration. The image is taken from a PA view. | PA | [
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00000003_004.png | This photo of a chest x-ray shows a Hernia finding. The image is taken from a PA view. | PA | [
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00000003_005.png | This photo of a chest x-ray shows a Hernia finding. The image is taken from a PA view. | PA | [-0.03054821863770485,0.031076371669769287,-0.2557828426361084,-0.0308160949498415,-0.00539532024413(...TRUNCATED) | [-0.02361217513680458,0.0213457178324461,-0.031623583287000656,-0.01281907968223095,-0.0238133706152(...TRUNCATED) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
00000003_006.png | This photo of a chest x-ray shows a Hernia finding. The image is taken from a PA view. | PA | [-0.0376569963991642,0.020924098789691925,-0.25126561522483826,-0.035456590354442596,0.0032629261258(...TRUNCATED) | [-0.02361217513680458,0.0213457178324461,-0.031623583287000656,-0.01281907968223095,-0.0238133706152(...TRUNCATED) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
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NIH-CXR14-BiomedCLIP-Features Dataset
This dataset is derived from the NIH Chest X-ray Dataset (NIH-CXR14) and processed using the BiomedCLIP-PubMedBERT_256-vit_base_patch16_224 model from Microsoft. It contains image and text features extracted from chest X-ray images and their corresponding textual findings.
Dataset Description
The original NIH-CXR14 dataset comprises 112,120 chest X-ray images with disease labels from 30,805 unique patients. This processed dataset includes:
- Image Features: Extracted using the vision encoder of BiomedCLIP (512 dimensions).
- Text Features: Extracted using the text encoder of BiomedCLIP (512 dimensions).
- Finding Labels: The original disease labels, processed and converted into a multi-label format.
- Image Index: Unique identifiers for each image.
- View Position: The view position of the X-ray (e.g., PA, AP).
- Processed Text: A grammatically correct text prompt generated from the finding labels, designed for use with the BiomedCLIP model.
Processing Steps
- Data Loading: The original NIH-CXR14 image and text datasets were loaded.
- Text Preprocessing:
- Problematic characters (
|) were replaced with commas. - "No Finding" labels were converted to "No_Finding".
- Finding labels were split into individual findings.
- Grammatically correct text prompts were generated based on the finding labels and view position.
- Problematic characters (
- Feature Extraction:
- Images and text prompts were preprocessed using the BiomedCLIP preprocessors.
- Image and text features were extracted using the BiomedCLIP model.
- Data Storage:
- Extracted features, image indices, view positions, raw texts, and finding labels were stored in Parquet files.
- The dataset was chunked into multiple Parquet files for efficient storage and retrieval.
Dataset Structure
The dataset is organized into Parquet files, each containing the following columns:
Image Index: String, unique identifier for each image.Image Features: List of floats, image features extracted by BiomedCLIP.Text Features: List of floats, text features extracted by BiomedCLIP.View Position: String, view position of the X-ray.Texts: String, processed text prompts.[Finding Label]: Integer (0 or 1), multi-label representation of each finding.
Usage
This dataset can be used for various tasks, including:
- Multi-label classification: Using the extracted features to predict disease findings.
- Retrieval: Retrieving relevant X-ray images based on text queries or vice versa.
- Fine-tuning: Fine-tuning models for medical image analysis tasks.
Installation
To load the dataset, you can use the datasets library from Hugging Face:
from datasets import load_dataset
dataset = load_dataset("Yasintuncer/NIH-CXR14-BiomedCLIP-Features")
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