MedLIFE A System for Medical Imagery Exploration Joshua

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Med-LIFE: A System for Medical Imagery Exploration Joshua New Erion Hasanbelliu Knowledge Systems Lab

Med-LIFE: A System for Medical Imagery Exploration Joshua New Erion Hasanbelliu Knowledge Systems Lab JN

Introduction • • What is Med-LIFE? What is image fusion? How do I teach

Introduction • • What is Med-LIFE? What is image fusion? How do I teach the computer? How can I view the results? Knowledge Systems Lab JN

What is Med-LIFE? • Med-LIFE is an application currently under development to use computer

What is Med-LIFE? • Med-LIFE is an application currently under development to use computer processing techniques to reduce medical personnel workload • GUI designed with Qt • Image Processing with C (and VTK library) Knowledge Systems Lab JN

What is Med-LIFE? • Consists of three processes (LIFE): – Learning of image attributes

What is Med-LIFE? • Consists of three processes (LIFE): – Learning of image attributes by the computer using SFAM – Image Fusion of many image modalities into one color image – Exploration of learning and fusion results Knowledge Systems Lab JN

What is Image Fusion? • Allows the combination of multiple image modalities into one

What is Image Fusion? • Allows the combination of multiple image modalities into one colored image with no information loss • Reduces workload by eliminating the number of images a radiologist must analyze • Images used from “The Whole Brain Atlas” – http: //www. med. harvard. edu/AANLIB/home. html Knowledge Systems Lab JN

What is image fusion? • Technique similar to primate vision Knowledge Systems Lab JN

What is image fusion? • Technique similar to primate vision Knowledge Systems Lab JN

Image Fusion Example PD GAD Color Fuse Result T 2 JN SPECT Knowledge Systems

Image Fusion Example PD GAD Color Fuse Result T 2 JN SPECT Knowledge Systems Lab

Image Fusion Example JN

Image Fusion Example JN

How do I teach the computer? • SFAM – Simplified Fuzzy ARTMAP • SFAM

How do I teach the computer? • SFAM – Simplified Fuzzy ARTMAP • SFAM is a computer-based system capable of online, incremental learning • Two “vectors” are sent to this system for learning: – Input feature vector tells what data is available from which to learn – Supervisory signal tells whether that vector is an example or counterexample Knowledge Systems Lab JN

How do I teach the computer? • Left-click to define examples (green) • Right-click

How do I teach the computer? • Left-click to define examples (green) • Right-click to define counterexamples (red) Main Window Zoom Window Knowledge Systems Lab JN

How do I teach the computer? • Supervisory signal from red/green marks • Feature

How do I teach the computer? • Supervisory signal from red/green marks • Feature vector from slice pixel values for original, single, and double opponent images Knowledge Systems Lab JN

Learning Results Main Window Results Zoom Window Results Knowledge Systems Lab JN

Learning Results Main Window Results Zoom Window Results Knowledge Systems Lab JN

Learning Results Main Window Results JN T 2 Knowledge Systems Lab

Learning Results Main Window Results JN T 2 Knowledge Systems Lab

How can I view results? • Display a plethora of information • Skull generated

How can I view results? • Display a plethora of information • Skull generated for patient from PD modality for contextual slice navigation • Explore tab provides several functions: – Original images – Fusion results imbedded within 3 D, patientgenerated skull – Learning results Knowledge Systems Lab JN

Demo Presentation • Erion will now demo the Med-LIFE system Knowledge Systems Lab JN

Demo Presentation • Erion will now demo the Med-LIFE system Knowledge Systems Lab JN

Conclusion • Med-LIFE offers reduced workload to physicians who scan multiple images – Image

Conclusion • Med-LIFE offers reduced workload to physicians who scan multiple images – Image processing and fusion reduces the number of images to be analyzed – Learning system allows the computer to perform prescreening or background analysis – Exploration allows immersion within the data for surgery planning Knowledge Systems Lab JN