Infusion Pump Equipment Image Dataset
#object detection #image classification #medical equipment detection #image recognition #automated diagnosis
- Records
- 5000 records
- Size
- 1.2G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
AI Analysis & Value Prop
The current medical industry faces numerous challenges in monitoring and managing infusion pump equipment, such as existing technologies failing to accurately identify equipment malfunctions and usage status, leading to medical incidents and resource waste. Existing solutions often rely on manual inspections, which are inefficient and prone to errors. This dataset aims to provide high-quality images of infusion pumps to support the training of object detection algorithms, thereby enhancing the automation and accuracy of equipment monitoring. The dataset includes images from multiple angles and environments to ensure diversity and representativeness. Data collection is conducted using high-resolution cameras in a standardized medical environment to ensure clear and usable images. We have implemented multiple rounds of annotation and consistency checks to ensure data accuracy and reliability. The data is stored in JPEG format and organized by category and environment for easy processing and retrieval.
Overview
Dataset Insights
Preview
Sample Examples
3c66d953**.jpg|1280*1493|191.89 KB
318e6be7**.jpg|1280*1696|157.00 KB
ad6d9916**.jpg|1280*1551|221.28 KB
1aea35a6**.jpg|1280*1592|181.93 KB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| device_model | string | The model of the infusion pump. |
| manufacturer | string | The name of the infusion pump manufacturer. |
| device_status | string | The current status of the infusion pump, such as normal, damaged, etc. |
| usage_environment | string | The environment in which the infusion pump is used, such as hospitals, laboratories, etc. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What tasks is this Intravenous Pump Device Image Dataset primarily used for?
- The Intravenous Pump Device Image Dataset is primarily used for object detection tasks, where models can identify and locate intravenous pump devices in images.
- In which healthcare fields is this dataset suitable for application?
- This dataset is suitable for applications in medical equipment monitoring, smart ward management, and medical image analysis, providing data support for improving the automation and management efficiency of medical equipment recognition.
- How can this dataset be used for intravenous pump object detection?
- This dataset can be used for intravenous pump object detection by building and training deep learning models that can detect and identify the position of intravenous pumps in images.
- What is the quality of the images contained in the Intravenous Pump Device Image Dataset?
- The dataset provides high-quality images, which is crucial for improving the accuracy and reliability of object detection algorithms.
- How can the importance of this dataset be evaluated in object detection projects?
- In the healthcare field, the importance of this dataset lies in enhancing the accuracy of automated device recognition, aiding in more effective device monitoring and management in medical environments.
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Cite this Work
@dataset{Mobiusi2025,
title={Infusion Pump Equipment Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/80b0fa59b9da0e5be8bda7cd46733d64?dataset_scene_id=4},
urldate={2025-10-22},
keywords={infusion pump dataset, medical image data, object detection dataset, medical equipment monitoring},
version={1.0}
}Using this in research? Please cite us.
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