VizChitra 2025

Abstract

Radiology generates vast amounts of complex image data daily. Radiologists’ primary role is to interpret these images accurately and efficiently. Globally, the aging population is rising, and the use of imaging as a critical diagnostic modality has exponentially increased, placing radiologists under immense time pressure.

This talk will explore how innovative data visualization techniques, powered by AI, can revolutionize radiology workflows, enhancing both automation and augmentation. We will understand the challenges of visualizing radiological data, including the intricacies of DICOM, the interpretation of multi-dimensional images (2D X-rays, 3D CT/MRI), and the need to represent temporal information. The presentation will showcase practical applications of data visualization, demonstrating how AI-driven tools can streamline measurements, highlight pathologies, and integrate seamlessly into the radiologist’s reporting process.

Attendees will gain insights into the potential of data visualization to improve diagnostic accuracy, reduce reporting times, and ultimately, enhance patient care.

Detailed Outline

• Introduction to Radiology Imaging

  • Brief overview of radiology and its importance.

  • Explanation of different imaging modalities

    • X-ray 2D imaging principles and applications.
    • CT (Computed Tomography) 3D imaging, cross-sectional anatomy.
    • MRI (Magnetic Resonance Imaging) 3D imaging, soft tissue contrast, functional information.
    • Temporal aspects in dynamic imaging studies.

  • Understanding DICOM

    • Introduction to the DICOM standard (storage, transmission).
    • Key DICOM elements relevant to data visualization.

• Navigating the 3D Space Anatomical Planes

  • Explanation of Sagittal, Axial, and Coronal planes.
  • Visualizing data across these standard planes.

• The Radiologist’s Challenge

  • Time pressures and high cognitive load.
  • Need for efficient tools for complex data interpretation.
  • Importance of accuracy and diagnostic confidence.

• AI-Powered Visualization: Automating and Augmenting Workflows

  • Role of AI in modern radiology.
  • How AI enables automation (routine tasks) and augmentation (interpretive support).

• Data Visualization Strategies in Radiology

  • Measurement Visualization
    • Challenges Displaying measurements clearly without obscuring image data.
    • Approaches Destructive vs. non-destructive overlays, annotations, interactive tools.
  • Visualizing AI Output
    • Challenge Integrating AI findings (often probabilistic) with grayscale images.
    • Methods Heatmaps, color overlays, contouring, transparency, confidence indicators.
  • Interactive Controls
    • Importance of user control over AI visualization layers (toggle on/off, adjust parameters).

• Use Cases

  • Automation: Quantifying Pathology
    • Example Automated measurement of bleed volume in CT brain scans.
    • Visualizing quantitative data Overlays on images, histograms, distribution plots.
  • Augmentation: AI-Assisted Diagnosis
    • Example AI detection of a subtle pathology (e.g., small lung nodule).
    • Visualizing AI findings Highlighting regions of interest, linking findings to the report, providing contextual information.

• Future work and next steps: Enriching the Workflow by Integrating Additional Data

  • Visualizing integrated data
    • Patient history and demographics.
    • Relevant lab results.
    • Prior imaging studies (longitudinal visualization).
    • Population statistics for comparison.
  • Future directions and potential impact.
  • Call to action for collaboration and further development.

Target Audience

This talk is designed as an introductory talk and is targeted towards a broad audience interested in data visualization, including

• Data scientists
• Visualization experts
• Healthcare professionals
• Medical imaging researchers
• Software developers

Anyone interested in the intersection of data visualization and medicine.

Speaker Bio

Bargava Subramanian has 20+ years of experience in Data Science and AI and works at the intersection of AI, Healthcare, and Product. He is currently building a startup in the medical imaging AI space. He holds a Master’s degree from the University of Maryland, College Park. Bargava has delivered numerous talks and conducted workshops at the Fifth Elephant Conference in Bangalore and O’Reilly’s Strata Conferences (NY/SF/London/Singapore). He also co-runs a community initiative supporting students in Government colleges across Tier-2 and Tier-3 cities in Tamil Nadu.