CHASE DB1 - Dataset Ninja

Introduction #

Muhammad Moazam Fraz, Paolo Remagnino, Andreas Hoppeet al.

The Child Heart and Health Study in England (CHASE), is a cardiovascular health survey across 200 primary schools in London, Birmingham, and Leicester. The retinal imaging was carried out in 46 schools and demonstrated associations between retinal vessel tortuosity and early risk factors for cardiovascular disease in over 1000 British primary school children of different ethnic origin. The retinal images of both of the eyes of each child were recorded with a hand-held Nidek NM-200-D fundus camera. The images were captured at 30 degree field-of-view with a resolution of 1280 × 960 pixels. The dataset of images are characterized by having nonuniform background illumination, poor contrast of blood vessels as compared with the background and wider arteriolars that have a bright strip running down the centre known as the central vessel reflex. This work is based on using a subset of images to create a retinal vessel reference dataset representing multi-ethnic school children known as CHASE_DB1. 28 retinal images are contained, acquired from both eyes of 14 children (8 white, 3 South Asian, 3 of other ethnic origin, mean age 10 years) recruited from one primary school in North-East London. For each image, there are two ground truths images for vessel segmentation made by two independent human observers.

File naming convention:

"01"-"14" = participant number.
"L" = left eye.
"R" = right eye.
"1stHO" = ground truth from first human observer.
"2ndHO" = ground truth from second human observer.

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Homepage

Research Paper

Summary #

CHASE DB1: Retinal Vessel Reference Dataset is a dataset for a semantic segmentation task. It is used in the medical research.

The dataset consists of 28 images with 28 labeled objects belonging to 1 single class (vessel).

Images in the CHASE DB1 dataset have pixel-level semantic segmentation annotations. All images are labeled (i.e. with annotations). There are no pre-defined train/val/test splits in the dataset. The dataset was released in 2012 by the Kingston University, London and St. George’s, University of London.

Here is the visualized example grid with animated annotations:

Explore #

CHASE DB1 dataset has 28 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

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Have a look at 28 images

View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 1 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Rows 1-1 of 1

Class ㅤ	Images ㅤ	Objects ㅤ	Count on image average	Area on image average
vessel➔ mask	28	28	1	6.93%

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Rows 1-1 of 1

Class	Object count	Avg area	Max area	Min area	Min height	Min height	Max height	Max height	Avg height	Avg height	Min width	Min width	Max width	Max width
vessel mask	28	6.93%	8.52%	5.06%	873px	90.94%	926px	96.46%	911px	94.87%	798px	79.88%	922px	92.29%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Objects #

Table contains all 28 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Rows 1-10 of 28

Object ID ㅤ	Class ㅤ	Image name click row to open	Image size height x width	Height ㅤ	Height ㅤ	Width ㅤ	Width ㅤ	Area ㅤ
1➔	vessel mask	Image_14R.jpg	960 x 999	905px	94.27%	798px	79.88%	5.85%
2➔	vessel mask	Image_14L.jpg	960 x 999	909px	94.69%	860px	86.09%	6.88%
3➔	vessel mask	Image_09R.jpg	960 x 999	911px	94.9%	882px	88.29%	5.09%
4➔	vessel mask	Image_02R.jpg	960 x 999	920px	95.83%	913px	91.39%	7.81%
5➔	vessel mask	Image_04R.jpg	960 x 999	926px	96.46%	887px	88.79%	7.7%
6➔	vessel mask	Image_03R.jpg	960 x 999	919px	95.73%	904px	90.49%	7.55%
7➔	vessel mask	Image_07R.jpg	960 x 999	924px	96.25%	915px	91.59%	7.61%
8➔	vessel mask	Image_08L.jpg	960 x 999	873px	90.94%	879px	87.99%	6.47%
9➔	vessel mask	Image_09L.jpg	960 x 999	900px	93.75%	821px	82.18%	5.06%
10➔	vessel mask	Image_10L.jpg	960 x 999	898px	93.54%	877px	87.79%	6.26%

License #

CHASE DB1: Retinal Vessel Reference Dataset is under CC BY 4.0 license.

Source

Citation #

If you make use of the CHASE DB1 data, please cite the following reference:

@dataset{CHASE DB1,
	author={Fraz, Muhammad Moazam and Remagnino, Paolo and Hoppe, Andreas and Uyyanonvara, Bunyarit and Rudnicka, Alicja R. and Owen, Christopher G. and Barman, Sarah A.},
	title={CHASE DB1: Retinal Vessel Reference Dataset},
	year={2012},
	url={https://researchdata.kingston.ac.uk/96/}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-chase-db1-dataset,
  title = { Visualization Tools for CHASE DB1 Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/chase-db1 } },
  url = { https://datasetninja.com/chase-db1 },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { nov },
  note = { visited on 2024-11-21 },
}

Download #

Dataset CHASE DB1 can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='CHASE DB1', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here:

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