Converting Medical Imaging Data into 3D Models

Biomodex
client

Client:

BIOMODEX
Medical Devices

Industry:

Medical Devices
core technologies

Core technologies:

Angular / RoR/ AWS
country

Country:

USA
Client Background

Client Overview

BIOMODEX is a digital health company dedicated to redefining physician training, patient-specific rehearsal, and pre-operative planning with proprietary 3D printing technology. The company approached Glorium Technologies to develop a software solution that would allow the team to print 3D anatomical models that mimic the structure, texture, and mechanical behavior of individual patient anatomy.
Challenge

Challenge

Medical 3D printing helps define surgical approaches, facilitates operational training and case-specific rehearsals, and provides doctors with realistic, practical experience.
The challenge in developing 3D models lies in the complexity and irregularity of human anatomy. Glorium Technologies’ principal responsibility was to ensure the precise identification and digital reconstruction of target anatomical structures from imaging data and to provide a smooth, accurate, and fast 2D-to-3D converting process.
Biomodex prod
Biomodex solution
Solution

Solution

Patient data obtained from non-invasive MRIs, CTs, or 3D ultrasounds is used to assist in detecting disease, abnormal anatomy, and deviations from the established, normal range of human physiology. The software we designed is able to:
Process the data from imaging studies
Precisely select the region of interest (body part)
Perform segmentation of DICOM images
Create STL for 3D printing
Features

Features

Order management system: Streamlining the process of requests and order tracking
Purchase and order management: Efficient handling of procurement and order fulfillment
DICOM series uploading: Facilitating the uploading of medical imaging data
Training workshops processing: Offering tailored solutions for training and rehearsal needs
DICOM viewer for STL files: Enabling detailed viewing of 3D models
Mapping 3D masks over organ images: Enhancing precision in model creation
Creation of STL for 3D printing: Facilitating the production of physical 3D models
Features
Business Value

Business Value

Boosting Productivity

Our software significantly improves workflows in medical imaging and 3D printing. By automating and optimizing the segmentation, analysis, and processing of high-resolution scans, we've automated segmentation tasks to create accurate 3D models.

This automation saves time and enhances the precision and quality of the printed models, crucial for medical training and pre-surgical rehearsals.

Integrating the AiPOD
Quick Start

One of the key factors in our successful collaboration with BIOMEDEX was our ability to mobilize rapidly. Within two weeks, we assembled a specialized team and initiated development, enabling the client to enter the market early.

BIOMODEX brought its solution to market ahead of competitors, securing early market positioning in the emerging medical simulation space.

target
Flexibility

Glorium Technologies focused on building a modular architecture. By integrating top frameworks for AQA processes, we ensured the software could adapt to evolving medical standards and requirements.

This adaptability is essential for BIOMODEX, allowing them to easily update or modify their offerings in line with the latest medical imaging technologies and printing techniques.

box
result
Results

Results

The upgraded software reduced the end-to-end conversion of medical imaging data into 3D models to just 30 minutes. This increased efficiency enabled BIOMODEX to rapidly produce highly accurate 3D printed models for surgical planning and training. A quick mobilization of the development team, speedy project initiation, and reduced production time gave the client a stronger market position.
The integration of flexible, advanced AQA frameworks ensured the software remained adaptable to the evolving needs of medical 3D printing. Consequently, BIOMODEX successfully commercialized this solution, establishing new benchmarks in medical training and preoperative preparation.

Tech Stack:

angular 1
Angular
Ruby
Ruby on Rails
aws 1
AWS