AI – Reading AssistentJanine Stucke-Ring, Productmanager

Alphatron Experience Day, 7th of November 2019

Introduction

Janine Stucke-Ring, PhD

Productmanager Radiology

AI – READING ASSISTENT

❖AI in medical imaging

❖AI Approaches

❖Objectives AI & Radiological Workflow

❖Challenges

❖Use case in JiveX

❖AI Marketplace

❖Conclusion

AGENDA

AI in medical imaging

VISUS Health IT

• The desire for greater efficiency in clinical care

• Grow of radiological imaging data -> less number of available trained readers

VISUS Health IT

AI Approaches – Radiological Workflow

Decisionto image

AutomatedAcquisition

(dose reduction)

Inpatientscheduling

Registration Detection, Segmentation, Quanitification

Decisionmaking

Synopticreporting

Harvey H.: „ Why AI will not replace radiologists“, in: Toward Data Science (2018), https://towardsdatascience.com/why-ai-will-not-replace-radiologists-c7736f2c7d80

AI APPROCHES

JIVEX PACS

VISUS Health IT

AI Approaches – JiveX PACS

JiveX PACS

Viewport

• Show results directly in the image

• Match with textbook information and process them

• Show data from other departments

Prior studies

• Recognize necessary prior studies

• Evaluate and analyze prior studies directly

• Compare data from other department (e.g. laboratory values)

Hanging Protocols

• Adjust hanging protocols to radiological workflow

• Case-related hanging protocols

Post Processing

• Directly trigger post processsing

• Display additional information on post-processing images

OBJECTIVES

AI

Less satisfaction of search

AI

Feedback- Loop

Objectives

AI

Integration of results into the report

AI

Structured findings with additional added value

KI

Structured findings with additional added value

Integration of results into the report

Useful visualization of results

Faster delivery of results

Feedback-Loops

Radiological Workflow

Satisfaction of search

VISUS Health IT

AI

Faster delivery of results

AI

Useful visualization of results

CHALLENGES

Challenges

• Partly missing legal requirements

• Additional processing of results can cost time

• Waiting of AI input

• Local AI Server can be expensive

(purchase/operate)

• Quality control

• Valid data and well annotated data

• Standardization

VISUS Health IT

HOW CAN THE APPLICATIONS

COME TO THE USERS?

VISUS Health IT

AI Use Case in JiveX

RIS

MR

JiveX PACS Jung

Diagnostics

HL7 Notification

Mail, DICOM Send

AI MARKETPLACE

VISUS Health IT

AI Marketplace

Use of an established network

VISUS Health IT

AI Marketplace

Implementation

PACS AI Service

Directory

Service

Mail Server

Central Service/ Adminstration

VISUS Health IT

AI Applications

FUSE-AIIntelligent analysis of medical imag

MERANTIX Healthcare

Image-centered oncological & neurological

diagnostic systems

MeVis

Computer-assisted analyzes

of lung CTs

Icometrix

Qualification of clinically

Relevant brain structures

UK Essen

Age determination based on the hand bones

Automated support of

detailed finding

UK Essen

Age determination based on the hand bones

Example 2017

Effort without AI

=217 hours per year

Effort with AI

=21,7 hours per year

Increase in efficency: 90%

VISUS Health IT

• One-time connection of the AI providers to the network

• Easy send of the examination to the AI service

• Automated return of the result

• Simple search of AI providers via a platform

• Simply booking the service via central service

provider

• Only one contractor

Advantages

CONCLUSION

VISUS Health IT

AI won’t replace radiologists but those radiologists who leverage the power of AI may replace those who don’t.

Mathias Goyen, GE Healthcare Chief Medical Officer

The Future Radiologist

Thank you