OCT data & Color Fundus Images of Left & Right Eyes
Donated on 10/31/2016
This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons.
Dataset Characteristics
Multivariate
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
50
# Features
-
Dataset Information
Additional Information
OCT data & Color Fundus Images of Left & Right Eyes : This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons. Each volunteer's folder includes color fundus images (.jpg) and OCT data (.mat) of the right and left eyes.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no |
0 to 2 of 2
Additional Variable Information
OCT data & Color Fundus Images of Left & Right Eyes : This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons. Each volunteer's folder includes color fundus images (.jpg) and OCT data (.mat) of the right and left eyes.
Dataset Files
| File | Size |
|---|---|
| HTOSMHP8 | 20.2 KB |
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset oct_data_color_fundus_images_of_left_right_eyes = fetch_ucirepo(id=430) # data (as pandas dataframes) X = oct_data_color_fundus_images_of_left_right_eyes.data.features y = oct_data_color_fundus_images_of_left_right_eyes.data.targets # metadata print(oct_data_color_fundus_images_of_left_right_eyes.metadata) # variable information print(oct_data_color_fundus_images_of_left_right_eyes.variables)
Akhlagi, T. (2014). OCT data & Color Fundus Images of Left & Right Eyes [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5KP5Z.
Creators
Tahereh Akhlagi
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.