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Dataset Card for "brain-tumor-image-dataset-semantic-segmentation"
Dataset Description
The Brain Tumor Image Dataset (BTID) for Semantic Segmentation contains MRI images and annotations aimed at training and evaluating segmentation models. This dataset was sourced from Kaggle and includes detailed segmentation masks indicating the presence and boundaries of brain tumors.
This dataset can be used for developing and benchmarking algorithms for medical image segmentation, particularly in identifying and segmenting brain tumors.
Features
Field Name | Data Type | Description | Example Value | Usage |
---|---|---|---|---|
file_name |
String | Name of the image file | "2256_jpg.rf.3afd7903eaf3f3c5aa8da4bbb928bc19.jpg" | Reference to the image file |
image |
Image | Image data | <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x640> |
Input for image analysis |
id |
Integer | Unique identifier for each image | 0 | Image-level identification |
category_id |
ClassLabel | Class label indicating if the image is of a tumor or not | 1 (where 0 = 'Tumor', 1 = 'Normal') | Classification of the image |
bbox |
List[Float] | Bounding box coordinates for the tumor | [145.0, 239.0, 168.75, 162.5] | Object detection, region of interest |
segmentation |
List[List[Float]] | Segmentation mask coordinates for the tumor | [[313.75, 238.75, 145.0, 238.75, 145.0, 401.25, 313.75, 401.25, 313.75, 238.75]] | Detailed object segmentation |
area |
Float | Area covered by the tumor | 27421.875 | Feature for analysis |
iscrowd |
Integer | Indicates if the segmentation mask is for a crowd | 0 | Binary flag for single object/crowd |
height |
Integer | Height of the image | 640 | Image dimension |
width |
Integer | Width of the image | 640 | Image dimension |
date_captured |
String | Date when the image was captured | "2023-08-19T04:37:54+00:00" | Metadata for the image |
license |
Integer | License information for the image | 1 | License reference for usage rights |
This table provides a clear and concise description of each field, its data type, an example value, and its usage within the dataset.
Data Splits
The dataset is split into three subsets:
- Train: 1502 images
- Validation: 429 images
- Test: 215 images
Example Usage
Here is how you can load and visualize the dataset using the Hugging Face datasets
library:
from datasets import load_dataset
dataset = load_dataset("dwb2023/brain-tumor-image-dataset-semantic-segmentation")
image = dataset["train"][0]["image"]
image.show()
Citation
Please cite the original creator of the dataset:
@dataset{Darabi2023BrainTumor,
author = {Peyman Darabi},
title = {Brain Tumor Image Dataset : Semantic Segmentation},
month = aug,
year = 2023,
url = {https://www.kaggle.com/datasets/pkdarabi/brain-tumor-image-dataset-semantic-segmentation},
note = {The Tumor Segmentation Dataset is designed specifically for the TumorSeg Computer Vision Project, which focuses on Semantic Segmentation. The project aims to identify tumor regions accurately within Medical Images using advanced techniques. The dataset contains two classes: Tumor (Class 1) and Non-Tumor (Class 0).},
}
License
The dataset is licensed under CC BY-NC 4.0. For more information, visit this link.
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