Shoulder Implant X-Ray Manufacturer Classification
Donated on 5/19/2020
597 de-identified raw X-ray scans of implanted shoulder prostheses from four manufactures.
Dataset Characteristics
Multivariate
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
Real
# Instances
597
# Features
1
Dataset Information
Additional Information
Images were collected by Maya Stark at BIDAL Lab at SFSU for her MS thesis project. They are from The UW Shoulder Site (http://faculty.washington.edu/alexbert/Shoulder/CommonUSShoulderProstheses.htm), manufacturer websites, and Feeley Lab at UCSF. The original collection included 605 X-ray images. Eight images that appeared to have been taken from the same patients were removed, resulting in the final 597 images. The final set contains images from the following manufacturers: 83 from Cofield, 294 from Depuy, 71 from Tornier, and 149 from Zimmer, resulting in a 4-class classification problem. Class labels are provided as the manufacturer name in file names.
Has Missing Values?
No
Variable Information
Images are with 8-bit grayscale and various dimensions in jpeg format.
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset shoulder_implant_x_ray_manufacturer_classification = fetch_ucirepo(id=517) # data (as pandas dataframes) X = shoulder_implant_x_ray_manufacturer_classification.data.features y = shoulder_implant_x_ray_manufacturer_classification.data.targets # metadata print(shoulder_implant_x_ray_manufacturer_classification.metadata) # variable information print(shoulder_implant_x_ray_manufacturer_classification.variables)
Shoulder Implant X-Ray Manufacturer Classification. (2020). UCI Machine Learning Repository. https://doi.org/10.24432/C5F893.
@misc{misc_shoulder_implant_x-ray_manufacturer_classification_517,
title = {{Shoulder Implant X-Ray Manufacturer Classification}},
year = {2020},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5F893}
}Keywords
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.