Healthcare today is all about data—collected from patients, providers, medical devices, and IoT sensors.
This data, whether it’s text, images, or videos, helps providers make informed decisions and improve patient outcomes.
But when it comes to managing and sharing medical images, things get complicated.
Medical images come in different formats and need to be converted to a standard like DICOM to ensure smooth sharing and interoperability.
This is where 3D medical imaging software becomes a game changer.
It not only allows for precise visualizations but also enhances diagnostic accuracy and patient care.
As we step into 2024, more healthcare providers and innovators are looking to build their own 3D imaging solutions.
This guide will walk you through the key steps of developing 3D medical imaging software, from choosing the right technology stack to ensuring compliance with industry standards.
What is 3D Medical Imaging Software?
3D medical imaging software is designed specifically for processing scans like CT, MRI, and PET.
It creates detailed 3D models of the body’s internal structures, which doctors use for diagnosis, treatment planning, and even surgical simulations.
This type of software brings two-dimensional medical images to life by offering virtual 3D models, adding depth and detail.
It allows physicians to make better diagnoses, streamline surgical planning, and reduce both operational costs and image acquisition times.
Whether it’s for complex surgeries or detailed clinical analysis, medical professionals across specialties benefit from this advanced visualization technology.
With the rapid advancements in 3D technology and artificial intelligence, the way medical images are managed, processed, and analyzed has been completely transformed.
For example, many dental imaging solutions now offer 3D visualization, and some systems even source images from vendor-neutral archives (VNA).
To qualify as medical 3D visualization software, the solution must:
- Generate 3D models of medical images
- Analyze images using deep learning technology
- Store, share, and provide access to these 3D images
Popular software in this space includes OsiriX, 3D Slicer, Amira, Mimics, and ITK-SNAP.
Medical Imaging Software Market Size
The demand for medical imaging software is growing rapidly across various healthcare fields like dental, cardiology, orthopedics, mammalogy, and urology.
By 2029, the global market for medical imaging software is expected to hit nearly $12 billion. This growth reflects a compound annual growth rate (CAGR) of 7.84%.
Focusing specifically on 3D medical imaging, the market was valued at $4.02 billion in 2022.
It’s projected to reach $7.16 billion by 2031, with a CAGR of 6.61% from 2023 to 2031.
The rising interest from radiologists and the growing use of 3D reconstruction in medical imaging are key factors driving this demand.
Introduction to DICOM and Its Importance in Medical Imaging
DICOM, or Digital Imaging and Communication in Medicine, is a set of standards that dictates how medical images are communicated and managed across different systems.
Its primary goal is to ensure interoperability between systems that handle medical images, ensuring smooth communication and sharing.
Without DICOM, healthcare and imaging systems would store and manage clinical images in their own formats, leading to major interoperability issues when transferring these images between systems.
Imagine trying to share MRI results from one provider to another, only to find that they can’t open the file because it’s in a different format.
To understand how DICOM works in practice, let’s consider the example of a patient undergoing an MRI.
In this case, two types of data are being generated: text-based data and visual data (the MRI images).
Text-based data is managed using the HL7 protocol, while the DICOM protocol is responsible for managing the images.
Thanks to DICOM, transferring MRI images from the MRI machine to a storage system and then accessing them from a workstation is not only easier but also more secure.
Moreover, it enables sharing these images seamlessly with external healthcare providers, improving patient care coordination.
Inside Our 3D Medical Imaging Software Development: A Case Study
We recently developed an advanced 3D medical imaging software for a healthcare technology firm.
Our solution focuses on reconstructing bones, skin, and various organs from X-rays and CT scans, utilizing cutting-edge machine learning techniques.
Solution
We incorporated medical imaging analysis into the client’s system, ensuring it was compatible with X-rays and CT scans from various specialties, including radiology and cardiology.
This integration allows 3D medical images to be accessed seamlessly across hospital workstations and personal laptops.
Functionality
1. 3D Rendering for X-rays & CT scans
Converting black-and-white images into 3D models is quick and easy. After uploading an X-ray or CT scan, clinicians can adjust settings to define 3D detail.
The platform scans and creates voxels, reconstructing denser body parts into volumetric images.
Once rendered, clinicians can use a toolbar to zoom in/out, add or remove skin, tissue, muscles, and bones, and trim excess parts.
A cube tool allows rotating the image for a clearer view of the pathology.
2. Compatibility and security for DICOM files
We first ensured the web platform seamlessly handles DICOM files, the standard for medical imaging. Then, we enhanced security to protect sensitive health information.
Our developers created a secure storage solution for imported DICOM files, including patient details, diagnoses, treatments, dates, and test results.
3. ROI manager for highlighting pathologies
Our team created a sophisticated ROI manager for highlighting pathologies.
Doctors can quickly identify and outline tumors in 3D models and measure lesion sizes for better surgical planning.
We also enabled precise segmentation by setting thresholds and pixel values, which helps in detailed 3D customization.
This includes generating reports with anatomical annotations and organ distance measurements. Additionally, practitioners can export and share 3D images based on user permissions.
How We Can Help You Build Your Own 3D Medical Imaging Software
In this project, we assembled a talented team of 12 specialists, including front-end and back-end developers, ML engineers, QA experts, and a UX/UI designer.
Over a 3-month development journey, we utilized a robust tech stack featuring Python, FastAPI, PyQt, JavaScript, React, MS SQL Server, and a variety of machine learning frameworks such as PyTorch and TensorFlow. AWS services were also integral to our solution.
Our services include:
- Custom Software Development: Tailored to meet your specific needs.
- Backend Development: Providing a strong foundation for your application.
With over 10 years of expertise, our comprehensive approach can help you build a sophisticated 3D medical imaging solution that meets industry standards and enhances diagnostic capabilities.
