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[An Intelligent Method for Optimizing Large-volume Medical Image Transmission].

Jiaying Hu¹, Yi Wang¹, Ping He²

¹Fudan University Shanghai Cancer Center, Shanghai, 200032.

Zhongguo Yi Liao Qi Xie Za Zhi = Chinese Journal of Medical Instrumentation

|February 8, 2023

Summary

This study introduces an intelligent method for efficient medical image transmission, significantly reducing data transfer needs. The approach prioritizes critical image data, ensuring physicians receive essential information for diagnosis with minimal data volume.

Keywords:

image segmentation medical image transmission neural networks transmission priority

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Area of Science:

Medical imaging
Artificial intelligence
Data transmission

Context:

Medical image transmission faces challenges with large data volumes, impacting supply and demand.
Current transmission methods are often inefficient for clinical needs.

Purpose:

To develop an intelligent method for efficient large-volume medical image transmission.
To optimize medical image transmission by prioritizing essential data for radiological reading and diagnosis.

Summary:

The method analyzes diagnostic reports to extract keyword pairs.
A 3D-UNet segments medical images based on anatomical structure.
Sub-areas are scored and prioritized for transmission, reducing data volume by 90%.

Impact:

Achieves efficient medical image transmission, fulfilling physician diagnostic requirements.
Significantly optimizes traditional medical image transmission procedures.
Reduces data transmission by 90% while maintaining diagnostic accuracy.