Infusion Scene Environment Classification Image Dataset
#Image Classification #Deep Learning Training #Medical Image Analysis #Infusion Monitoring #Clinical Decision Support
- Records
- 5000 records
- Size
- 1.2G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-04
AI Analysis & Value Prop
The current medical industry faces challenges of insufficient image data and low annotation quality in the environmental classification of infusion scenes. Existing solutions largely rely on manual annotation, which is inefficient and prone to errors. This dataset aims to solve image recognition problems in the infusion environment classification by providing high-quality annotated data to meet the needs of clinical decision support and medical image analysis. Data collection uses professional medical imaging equipment, covering infusion scenes in different hospitals to ensure diversity and representativeness. Multiple rounds of review and expert evaluation were implemented during the annotation process to ensure annotation consistency and accuracy. Data is stored in JPG format and organized by category to facilitate subsequent model training and application.
Overview
Dataset Insights
Preview
Sample Examples
1f701abe**.jpg|1280*1706|324.35 KB
e8405cbf**.jpg|1280*1706|335.83 KB
3b01818e**.jpg|1280*1706|456.22 KB
356a32a8**.jpg|1080*1421|197.66 KB
d92d87e5**.jpg|1080*1440|129.15 KB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| scene_type | string | Identify the specific type of infusion scene, such as operating room, ward, etc. |
| device_presence | boolean | Identify whether there are medical devices present in the image. |
| personnel_presence | boolean | Identify whether there are personnel present in the image. |
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 different infusion scenarios does this dataset include?
- The dataset includes images of various infusion scenarios, such as hospital wards and clinic environments.
- What research areas is the Infusion Scene Environment Classification Image Dataset suitable for?
- This dataset is suitable for medical image analysis, machine learning model training, and computer vision research.
- How can this dataset be used for training deep learning models?
- The infusion scenario images provided can be used to train deep learning models to enhance their ability to recognize medical contexts.
- Are the images in the dataset labeled?
- Yes, the images in the dataset are labeled, divided into different scenario categories.
- How do you evaluate the value of this dataset in the healthcare field?
- This dataset has significant value in medical image analysis and model training, helping to improve the quality of healthcare services.
- What should be considered when using the Infusion Scene Environment Classification Image Dataset?
- When using this dataset, it is important to protect patient privacy and adhere to relevant laws and regulations.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
High-quality data, ready for your next AI breakthrough.
Cite this Work
@dataset{Mobiusi2025,
title={Infusion Scene Environment Classification Image Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/ef11bf2f833da0accfea9b34d5e35012?dataset_scene_id=4},
urldate={2025-10-22},
keywords={Infusion Scene Image Dataset, Medical Image Classification, Deep Learning Medical Data},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder