SoQut Imaging

Elibio

When growth and product value are deeply intrecated.

SoQut Imaging developed an innovative MRI sequence designed to support liver disease assessment. But transforming scientific technology into a product healthcare professionals would actually use required more than building an interface. I led product discovery and experience design, working alongside scientists and medical professionals to define the MVP, challenge assumptions, and design workflows grounded in clinical practice.

Client

SoQut Imaging

Year

2026

Role

Scope

User Research · Product Discovery · Product Strategy · UX/UI Design · Usability Testing · Design Leadership

Location

Bègles, France

Project Status

Design delivered. Development in progress.

Main image showcasing the project.
Main image showcasing the project.
Main image showcasing the project.
Main image showcasing the project.
Main image showcasing the project.

DESIGN PROBLEM

The product is currently under development. Clinical adoption and commercial outcomes have not yet been measured.

A scientific breakthrough

A scientific breakthrough

A scientific breakthrough

Technology alone doesn’t guarantee adoption. SoQut Imaging had developed an MRI acquisition sequence capable of producing quantitative liver data. The challenge was to build the software that would allow healthcare professionals to process, interpret, and reuse those results.
My mission was to help the team move from a technology-driven vision to a product grounded in real-world clinical practices.

RESULTS

Product strategy

An evidence-informed MVP

Defined priority workflows and features based on clinical needs, market differentiation, and operational constraints.

Design delivery

A tested product experience

Delivered tested interaction designs, UI screens, prototypes, and handoff documentation for development.

Team enablement

A more autonomous scientific team

Introduced user research practices and progressively enabled scientific team members to conduct interviews and usability tests independently.

USE CASE

Designing around clinical reality.

Designing around clinical reality.

Designing around clinical reality.

Early discussions focused primarily on radiologists and hepatologists. We were designing for the wrong user. The initial assumptions didn’t reflect how radiology departments actually worked.

Challenge

Great technology doesn’t guarantee adoption.

The MRI sequence already existed. The software to exploit its results didn’t.

The challenge was to define a product that medical professionals would adopt alongside established tools, while preserving the scientific reliability of its measurements.

Problem

the market already relied on established tools and deeply ingrained workflows.

Why would medical professionals adopt another piece of software ? And, more importantly, how could we design a product that respected clinical responsibilities without adding unnecessary complexity?

Approach

01 — Discovering the real workflow

Research revealed that radiology technologists (not just radiologists) played a central role in image processing.

We also found that existing workflows were fragmented, and that automation could sometimes create more work than it saved.

Decision: Prioritize radiology workflows, support different professional practices, and focus the MVP on essential Jobs to Be Done.

02 — Balancing usability and scientific reliability

A fixed number of image slices couldn’t account for variations in liver morphology.

Decision: Replace a rigid segmentation rule with visible information about the liver volume covered, allowing operators to exercise their judgment.

03 — Making technical decisions explicit

Usability tests exposed difficulties editing anatomical contours. Investigating the issue revealed that the curve algorithm itself influenced how operators controlled the result.

Decision: After comparing alternatives through prototypes, we selected Catmull-Rom with the Scientific Director to preserve user-defined control points.

04 — Testing assumptions, not just interfaces.

Early usability tests revealed confusing terminology, technically driven workflows, and segmentation controls that were difficult to discover.

Decision : We simplified interactions, reconsidered hidden controls, and adapted the experience to the different working conditions of radiologists and technologists.

Approach

01 — Discovering the real workflow

Research revealed that radiology technologists (not just radiologists) played a central role in image processing.

We also found that existing workflows were fragmented, and that automation could sometimes create more work than it saved.

Decision: Prioritize radiology workflows, support different professional practices, and focus the MVP on essential Jobs to Be Done.

02 — Balancing usability and scientific reliability

A fixed number of image slices couldn’t account for variations in liver morphology.

Decision: Replace a rigid segmentation rule with visible information about the liver volume covered, allowing operators to exercise their judgment.

03 — Making technical decisions explicit

Usability tests exposed difficulties editing anatomical contours. Investigating the issue revealed that the curve algorithm itself influenced how operators controlled the result.

Decision: After comparing alternatives through prototypes, we selected Catmull-Rom with the Scientific Director to preserve user-defined control points.

04 — Testing assumptions, not just interfaces.

Early usability tests revealed confusing terminology, technically driven workflows, and segmentation controls that were difficult to discover.

Decision : We simplified interactions, reconsidered hidden controls, and adapted the experience to the different working conditions of radiologists and technologists.

OUTCOME & LEARNINGS

Building reasearch autonomy beyond the project.

Building reasearch autonomy beyond the project.

I involved scientific team members in field research, introduced usability testing practices, and progressively transferred responsibility. By the final sessions, team members were able to conduct some parts of the interviews and tests themselves.

Research framing

Making research priorities explicit.

Co-created interview guides with scientific experts, prioritizing questions by criticality and availability of secondary evidence to make the most of limited clinical access.

Collaborative fieldwork

Combining expertise with research rigor.

Coached team members on interviewing practices, consistent protocols, and when to introduce expert follow-up questions without disrupting participants.

Knowledge transfer

Enabling independent research.

Progressively involved scientists in conducting interviews and usability tests, until team members could lead sessions themselves.

REFLEXION

Good design leadership isn’t about owning every decision.

Good design leadership isn’t about owning every decision.


It’s about connecting expertise, evidence, and constraints so teams can make better decisions together.

The product is still in development. But beyond delivering its design, I helped build the foundations for a team that could continue learning from users independently.

VISUALS

From research
to interaction design.