---
AI Summary: "\\- Developed a React web UI, Python web server, and Python image‑processing\
  \ server integrated with Orthanc for DICOM handling.  \n- Automated mapping of DICOM\
  \ metadata to processing profiles and performed image reorientation, reslicing,\
  \ and resampling.  \n- Delivered a full‑cycle SaMD and achieved FDA 510(k) clearance\
  \ within 14 months."
Anonymous: false
Assignee:
- Matt Hancock
Last Edited Time: '2026-01-25T23:06:00+00:00'
case_study_510ks:
- 1f4bd5b7-a754-8015-bc4e-dc466feee1a8
client_logo:
- 18dbd5b7-a754-80ea-8027-e8c7af8aa3fd
client_name: RadUnity
date: '2024-11-27'
featured: true
medical_panel: Radiology
name: We Built a Radiology Workflow Tool and Got It FDA Cleared in 14 Months
services:
- 9dc4f55a-b5cb-419f-8bae-5e11d6b11fee
- 6d5e46e7-72da-4217-bdd9-c1c771f2f696
summary: 'Built and cleared a DICOM image processing SaMD in 14 months. Full-cycle:
  engineering to 510(k) clearance.'
tags:
- Web-App
- Image Processing
- DICOM
- 510k
testimonials:
- 60943488-d515-476f-8e35-391aaac2b7bb
---

## The Problem

In radiology, the variability in imaging parameters across different CT scanners and clinical sites leads to inconsistent image presentations. This inconsistency forces radiologists to adapt to varying image qualities and presentations, potentially leading to inefficiencies, fatigue, and challenges in accurate diagnosis. The solution aims to standardize image presentation, streamline workflow, and enhance radiologists\' efficiency.

## What We Did

Together with the RadUnity team, we developed a software medical device designed to aid in the management and processing of CT images. We also prepared the FDA 510(k) submission, performed software validation, and implemented cybersecurity controls necessary for a successful 510(k).

## Key Accomplishments

- Built a data-intensive web application capable of:
  - Sending/receiving DICOM CT images
  - Automatically mapping DICOM metadata to pre-configured image-processing configurations
  - Performing image processing jobs on DICOM image data (to reorient, reslice, and resample images)
  - Presenting processing status and user configurations in a modern web UI dashboard
- Completed the full software engineering lifecycle and achieved 510(k) clearance within 14 months.

<figure>
  <img src="/img/portfolio/We_Built_a_Radiology_Workflow_Tool_and_Got_It_FDA_Cleared_in_14_Months-144bd5b7a75480df86b2e9bc5727198a.png">
  <figcaption>
    Clinicians are shown a dashboard, displaying the status of received
    DICOM data, and allowing them to take any needed actions.
  </figcaption>
</figure>

<figure>
  <img src="/img/portfolio/We_Built_a_Radiology_Workflow_Tool_and_Got_It_FDA_Cleared_in_14_Months-144bd5b7a75480d797f0c6881d2ec404.png">
  <figcaption>
    Administrative users configure “mappings” that are used to automatically
    link DICOM data received by the application with a “profile” of image
    processing configurations. E.g., a Chest CT might be configured to
    automatically produce axial and coronal views with certain desired slice
    thicknesses.
  </figcaption>
</figure>

<figure>
  <img src="/img/portfolio/We_Built_a_Radiology_Workflow_Tool_and_Got_It_FDA_Cleared_in_14_Months-144bd5b7a75480c7a0b5fc65c55d19bb.png">
  <figcaption>
    A user can select a subset of the extent of a CT scan to be processed
    using sliders in a coronal view (shown in the center). Previews in the
    axial plane for the endpoints of the selected extent and midpoint are
    displayed (shown on the right).
  </figcaption>
</figure>

## Key Technologies

- A modern React-based web UI
- A Python-based web server
- A Python-based image-processing server
- An Orthanc-based DICOM sender/receiver

## Timeline

October 31, 2023: Scoping and strategy complete

November 30, 2023: Presubmission meeting

February 4, 2024: Backend implementation complete

May 1, 2024: Frontend implementation complete

September 18, 2024: 510(k) Submitted

November 26, 2024: 510(k) Cleared!