How Axial3D leverages AWS to help surgeons improve outcomes with 3D medical models
Axial3D helps surgeons save lives using detailed pre-operative 3D medical models. Using AWS, Axial3D creates and delivers 3D printed models in a day or two, a task that previously would have taken up to eight weeks. An AWS Partner Network (APN) Public Sector Partner, Axial3D used Amazon SageMaker, Amazon EC2, and Amazon S3 to help surgeons at Belfast City Hospital successfully perform a kidney transplant that saved two lives.
Across the globe, surgeons are increasingly using 3D printed anatomical models to prepare for complex operations by creating detailed surgical plans. However, the process of segmenting 2D images into multiple labeled regions to produce a 3D model is often time-consuming, requiring clinicians to be away from treating patients.
Axial3D, a medical 3D printing technology provider, aims to solve this problem. The company offers patient-specific, accurate 3D printed models that can be created quickly. “We specialize in converting images to 3D-printed files that surgeons use for preoperative planning when they need a better understanding of surgeries,” says Daniel Crawford, founder and chief strategy officer for Axial3D.
An APN Select Technology Partner and a member of the Public Sector Partner Program, Axial3D runs its web-based 3D modeling application on AWS. Crawford says, “Using AWS, we have the agility and scalability we need to offer our customers fast access to high-quality 3D printing.”
Axial3D relies on Amazon Elastic Compute Cloud (Amazon EC2) to host its web platform, which surgeons use to easily and quickly place orders for a 3D printed model. Axial3D uploads 2D images from MRI or CT scans to Amazon Simple Storage Service (Amazon S3) and then runs machine learning models based on Amazon SageMaker. “Using Amazon SageMaker, we can quickly deploy new models and perform fast inference of large medical image datasets,” says Crawford.
Read the full story, and discover how an Axial3D model helped a surgeon save two lives on the AWS blog.
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