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Designing an 'intelligent' ultrasound software to enable novice clinicians into taking better quality scans 
CHALLENGE
Currently, due to the large learning curve in ultrasound technology and interpretation, access is limited to highly trained professionals. This in turn delays patient care and increases cost of diagnosis.
DURATION
1 Year
IMMEDIATE TEAM
Design: Ching Hsieh
PM: Ali Chaudhry, Stephen Aman
Engineering: Laura Piersall, Erin McCarty
Clinical: Patrick Brown, Sara Guttas
TOOLS
Research: Fly on the wall, Contextual Inquiry, Empathy Mapping, Service Blueprinting
Design: Sketch, Adobe Illustrator, Principle
User Testing: Qualitative Interviews and Observation
 
RESPONSIBILITIES
Collaboration with clinical teams to understand problem space; Working on user flows and UI Design; Research and testing with doctors and clinicians; Coordinating with Engineering and QA team for product launch; Managing design efforts with an external agency for the launch of a new product line.

"The biggest takeaways while working on the product were the direct results and visibility of impact that were enabled by intuitive design."

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"Ultrasound machines are too complicated"
Conventional ultrasound relies on an expert eye to recognize anatomical structures, limiting access to a subset of clinicians with years of specialized training. Caption AI helps 'simplify' these functions using a user friendly interface.
"Where do I even start??"
For each view, Caption AI provides a probe positioning diagram indicating where and how to place the probe. A reference image provides a visual example of what to look for while scanning.
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"I would definitely need training to do this"
Caption AI emulates the guidance of an expert sonographer by providing real-time feedback and adaptive instructions, which prompt users to make specific transducer movements to optimize and capture a diagnostic-quality image.
"Is this image good enough?"
The Quality Meter lets users see in real time how close they are to capturing a diagnostic-quality image. The meter rises as the user gets closer to the optimal view, turning green when the image is deemed diagnostic. AutoCapture then records the clip, hands-free.
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"Can I go back to where I was?"
Caption AI continuously keeps track of the best images seen during each scanning session so the best image from each view is automatically captured. Users have the freedom to explore each view with the reassurance that they can always access the best clip seen during their scan.

I would love to chat more regarding my in-depth process.

If you're interested, please contact me at tithi.jasani93@gmail.com or using the form below. 

Thanks for reaching out!

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