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Immersive Visualization of Brain Lesions

At a Glance

Researchers at Colorado State University have developed a new system that uses artificial intelligence and virtual reality to create 3D views of brain scans. This system helps doctors and patients better understand brain lesions by allowing them to see the affected areas in an immersive 3D environment, instead of just flat 2D images. This innovative approach makes it easier to grasp the size, shape, and location of abnormalities in the brain; aiming to improve diagnosis and patient communication for neurological conditions.

Background

Traditional MRI scans are typically viewed in 2D slices, which makes it difficult to fully understand the shape, size, and impact of brain lesions. Deep learning techniques have improved segmentation accuracy, but the resulting images still lack context for medical professionals and patients. Virtual reality (VR) can fill this gap by turning flat images into interactive 3D experiences.

Overview

This new technology takes standard MRI brain scans and makes them easier to understand by using artificial intelligence and virtual reality. First, a deep learning model is trained on almost a million MRI images to recognize patterns in medical images and identify abnormal areas in the brain such as tumors or injuries. Once those areas are identified, the system turns the 2D scan images into a 3D model of the brain. This model can be explored using a virtual reality headset, allowing doctors—or even patients—to look inside the brain and examine it from different angles. They can zoom in, move around the scan, and view slices of the brain in real time. This creates a much clearer picture of what’s happening inside the brain, which could lead to faster diagnoses, better treatment decisions, and improved patient understanding of their condition.

Figure 1. A user can view specific slice renders along the different planes of the brain, along with the 3D rendering

Benefits

  • Improved Spatial Understanding: Provides an interactive 3D volumetric view of brain lesions, enhancing comprehension of size, shape, and relationship to surrounding tissue compared to 2D cross-sections
  • Enhanced Communication: Offers a tool for medical professionals to explain diagnoses more effectively to patients through immersive visualization
  • High Differentiation Accuracy: The VGG-16 model trained on FLAIR MRI data shows a strong ability (98.28% precision) to distinguish between relevant lesion data and background pixels.
  • Leverages Existing Technologies: Integrates established deep learning models (VGG-16) and VR platforms (Unity Engine, Meta Quest 3)
  • Supports Early Intervention: Facilitates efficient and accurate diagnosis of potential issues, crucial for early intervention in life-threatening diseases

Applications

  • Medical diagnosis and consultation for neurological disorders.
  • Medical education and training for anatomy and pathology visualization.
  • Pre-surgical planning and visualization for neurosurgery.
  • Patient engagement and understanding of medical conditions.
  • Research and development in medical imaging and immersive analytics.
  • Telemedicine and remote consultations

Publications

B. Kelley, et al. (2025) “Segmentation and Immersive Visualization of Brain Lesions Using Deep Learning and Virtual Reality” VRCAI ’24: Proceedings of the 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry https://doi.org/10.1145/3703619.370603

Last Updated: July 2025
Opportunity

Available for Exclusive Licensing
TRL: 4

IP Status

Copyright/Software

Inventors

Brendan Kelley
Lucas Plabst
Lena Plabst

Reference Number
2025-038
Licensing Manager

Aly Hoeher
Aly.Hoeher@colostate.edu
970-491-7100

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