Revolutionizing Medical Imaging: From Two Phone Photos to 3D Diagnostic Models

How We Patented the Future of Mobile 3D Scanning

In the world of medical imaging and orthopedic assessment, precise 3D measurements have traditionally required expensive specialized equipment, controlled clinical environments, and trained technicians. We set out to change this paradigm entirely—developing a breakthrough AI algorithm that could create accurate 3D models of human feet and spines using nothing more than a smartphone camera and two simple angles.

The result was US Patent 11816806B2, a granted patent that represents a fundamental shift in how 3D medical scanning can be democratized and made accessible to millions of people worldwide.

The Problem: 3D Scanning Without 3D Hardware

Traditional 3D scanning in medical contexts requires sophisticated equipment—LIDAR sensors, structured light scanners, or multiple calibrated cameras in controlled environments. These solutions are expensive, require specialized training, and are typically confined to clinical settings. For conditions affecting feet and spines, patients often need to travel to specialized facilities for proper 3D assessment.

Our challenge was audacious: could we achieve the same diagnostic-quality 3D reconstruction using only the cameras that people already carry in their pockets? The technical hurdles were immense—smartphones lack dedicated depth sensors, have limited computational power, and operate in uncontrolled lighting conditions with untrained users.

The Breakthrough: Morphable Models Meet Mobile AI

Our patented approach combined several cutting-edge techniques into a unified system that could extract 3D information from minimal 2D inputs:

Two-Angle Capture Protocol: Instead of requiring dozens of images from multiple angles, our system needed only two strategic viewpoints—typically a top view and a side view. This dramatically simplified the user experience while providing sufficient information for accurate 3D reconstruction.

3D Morphable Model Foundation: The core innovation lay in our use of 3D morphable models—statistical representations of human anatomy that could be deformed and adapted to match individual variations. Rather than trying to reconstruct 3D geometry from scratch, our system fit these pre-trained models to the captured 2D data.

Iterative Closest Point (ICP) Optimization: Our algorithm used sophisticated ICP techniques to establish correspondences between the captured 2D data and our 3D morphable models, iteratively refining the fit until achieving optimal accuracy.

Technical Innovation: Point Clouds from Pixels

The heart of our patented system was the ability to generate accurate 3D point clouds from 2D smartphone images:

Convolutional Neural Network Segmentation: Our CNN-based segmentation system could precisely identify and isolate the foot or spine regions from smartphone photos, even in challenging lighting conditions or cluttered backgrounds.

Reference Object Scaling: To achieve accurate real-world measurements, our system incorporated a simple reference object (like a credit card or coin) that provided scale information, allowing the algorithm to convert pixel measurements into precise physical dimensions.

Multi-View Stereo Reconstruction: By combining information from our two strategic camera angles, the system could infer depth information and create detailed 3D point clouds that captured the essential geometric features needed for medical assessment.

The Patent: Protecting Innovation in Mobile 3D Scanning

US Patent 11816806B2 covers the fundamental methods and systems we developed for mobile 3D reconstruction:

Core Patent Claims: The patent protects our specific approach to:

• Capturing foot/spine data from strategic viewpoints using mobile devices
• Processing captured data to create point clouds via ICP transformation estimates
• Matching point clouds with average anatomical models to establish correspondences
• Calculating morphable models that fit individual user anatomy

Technical Scope: The patent covers both the hardware configurations (mobile devices with cameras and sensors) and the software algorithms (CNN segmentation, ICP optimization, morphable model fitting) that make the system work.

Broad Applications: While our initial focus was on feet and spines, the patent's scope extends to other anatomical structures that could benefit from mobile 3D scanning.

Medical Applications: Transforming Orthopedic Assessment

Our patented technology opened up new possibilities for medical diagnosis and treatment:

Podiatric Assessment: Accurate 3D foot models could help diagnose conditions like flat feet, plantar fasciitis, and other structural abnormalities without requiring expensive clinical equipment.

Orthotic Fitting: Custom orthotic devices could be designed based on precise 3D foot models, improving comfort and therapeutic effectiveness while reducing the need for multiple clinical visits.

Spinal Assessment: Early detection of spinal curvature issues like scoliosis could be performed using simple smartphone scans, enabling earlier intervention and better outcomes.

Remote Monitoring: Patients could track changes in their conditions over time using consistent 3D measurements, providing valuable data for ongoing treatment optimization.

Consumer Applications: Beyond Medical Use

The technology's potential extended far beyond medical applications:

Footwear E-commerce: Online shoe retailers could use our technology to provide perfect fit recommendations, reducing returns and improving customer satisfaction.

Custom Manufacturing: 3D foot models could enable mass customization of shoes, orthotics, and other products that require precise anatomical fit.

Fitness and Sports: Athletes could monitor foot mechanics and biomechanics using regular smartphone scans, optimizing performance and preventing injuries.

Accessibility: People with mobility limitations could access professional-quality 3D scanning from their homes, removing barriers to proper medical assessment.

Technical Challenges: Making It Work in the Real World

Developing a patentable system that worked reliably in real-world conditions required solving numerous technical challenges:

Lighting Variation: Smartphones operate in dramatically different lighting conditions. Our CNN segmentation needed to work equally well in bright outdoor light, dim indoor environments, and everything in between.

User Variability: Unlike clinical settings with trained technicians, our system needed to work with untrained users taking photos at inconsistent angles and distances. The algorithm had to be robust enough to extract accurate measurements despite significant input variation.

Computational Constraints: All processing needed to happen on mobile devices with limited computational power and battery life. This required extensive optimization of our algorithms to balance accuracy with performance.

Anatomical Diversity: Human anatomy varies significantly between individuals. Our morphable models needed to accommodate this diversity while maintaining accuracy across different foot shapes, sizes, and conditions.

The Path to Patent: From Research to Legal Protection

The journey from initial research to granted patent involved several critical stages:

Novelty Validation: We conducted extensive prior art searches to ensure our approach was genuinely novel and patentable. The combination of mobile 3D scanning, morphable models, and two-angle capture represented a unique innovation in the field.

Technical Documentation: The patent application required detailed technical descriptions of our algorithms, including mathematical formulations, system architectures, and implementation details that would allow others to understand and potentially implement the technology.

Claim Strategy: We worked with patent attorneys to craft claims that were broad enough to protect the core innovation while specific enough to be defensible and enforceable.

Regulatory Considerations: For medical applications, we ensured our patent claims were compatible with FDA and other regulatory requirements for medical devices and diagnostic tools.

Commercial Impact: Democratizing 3D Scanning

The granted patent represents more than just intellectual property—it's a foundation for democratizing access to sophisticated 3D scanning technology:

Market Disruption: By making 3D scanning accessible through smartphones, our technology could disrupt traditional medical imaging and custom manufacturing markets.

Healthcare Equity: Remote 3D scanning capabilities could bring advanced diagnostic tools to underserved communities and rural areas without access to specialized medical facilities.

Innovation Platform: The patent creates a platform for further innovation in mobile 3D scanning, enabling development of new applications and use cases.

Industry Licensing: Other companies could license our patented technology to integrate 3D scanning capabilities into their own products and services.

Looking Forward: The Future of Mobile 3D Scanning

Our granted patent represents just the beginning of what's possible with mobile 3D scanning:

Enhanced Accuracy: Future iterations could incorporate additional sensors and AI techniques to achieve even higher precision in 3D reconstruction.

Expanded Applications: The core technology could be adapted for scanning other body parts, objects, or environments where 3D information is valuable.

Integration Opportunities: The patent provides a foundation for integrating 3D scanning into existing medical, retail, and manufacturing workflows.

Regulatory Pathways: As a patented technology, it's better positioned for regulatory approval and clinical adoption in medical applications.

Technical Legacy: Beyond the Patent

The innovation represented by US Patent 11816806B2 extends beyond the specific technical claims:

Algorithmic Contributions: Our approach to combining morphable models with mobile computer vision has influenced broader research in 3D reconstruction and medical imaging.

User Experience Innovation: The two-angle capture protocol demonstrated that sophisticated 3D scanning could be made accessible to non-technical users.

Mobile AI Advancement: The project pushed the boundaries of what was possible with on-device AI processing, contributing to the broader field of mobile machine learning.

Interdisciplinary Impact: The work bridged computer vision, medical imaging, and mobile computing in ways that have influenced research across multiple fields.

Lessons in Innovation and IP Protection

Our experience developing and patenting this technology offers insights for other innovators:

Early IP Strategy: Beginning the patent process early in development helped protect our innovations while they were still novel and non-obvious.

Technical Depth: The patent's strength comes from the detailed technical innovations rather than just the high-level concept.

Broad Vision: Thinking beyond the immediate application helped us craft patent claims that cover a wide range of potential uses.

Regulatory Awareness: Understanding the regulatory landscape for medical devices informed both our technical development and patent strategy.

Reflecting on Mobile 3D Innovation

US Patent 11816806B2 represents a successful translation of research innovation into protected intellectual property with real-world applications. By solving the fundamental challenge of creating accurate 3D models from minimal 2D input, we've contributed to the democratization of 3D scanning technology.

The patent demonstrates that with the right combination of computer vision, machine learning, and mobile computing, it's possible to bring sophisticated medical and commercial capabilities to devices that people already carry. This represents a paradigm shift from expensive, specialized equipment to accessible, ubiquitous technology.

As 3D scanning becomes increasingly important across healthcare, e-commerce, and manufacturing, our patented approach provides a foundation for making these capabilities available to millions of people worldwide.

The future of 3D scanning isn't in specialized laboratories or clinical settings—it's in the pocket of every smartphone user, enabled by the kind of algorithmic innovation that transforms research breakthroughs into practical, patented solutions.