AI assisted method for efficiently generating breast ultrasound screening reports

TL;DR

This paper presents an AI-powered pipeline that automatically generates preliminary breast ultrasound screening reports, significantly enhancing clinical efficiency and reducing manual reporting workload.

Contribution

It introduces a novel AI-based method for automatic report generation tailored for breast ultrasound screening, especially for benign and normal cases, streamlining clinical workflow.

Findings

Improves doctors' work efficiency by up to 90%.

Reduces repetitive manual report writing.

Enhances acceptance of AI-generated reports in clinical practice.

Abstract

Background: Ultrasound is one of the preferred choices for early screening of dense breast cancer. Clinically, doctors have to manually write the screening report which is time-consuming and laborious, and it is easy to miss and miswrite. Aim: We proposed a new pipeline to automatically generate AI breast ultrasound screening reports based on ultrasound images, aiming to assist doctors in improving the efficiency of clinical screening and reducing repetitive report writing. Methods: AI was used to efficiently generate personalized breast ultrasound screening preliminary reports, especially for benign and normal cases which account for the majority. Based on the preliminary AI report, doctors then make simple adjustments or corrections to quickly generate the final report. The approach has been trained and tested using a database of 4809 breast tumor instances. Results: Experimental results indicate that this pipeline improves doctors' work efficiency by up to 90%, which greatly reduces repetitive work. Conclusion: Personalized report generation is more widely recognized by doctors in clinical practice compared with non-intelligent reports based on fixed templates or containing options to fill in the blanks.