MIST: Medical Image Streaming Toolkit

Architecture

A schematic representation of MIST's hierarchical and adaptive streaming pipeline.

MIST and ISLE represent two complementary frameworks addressing the challenges of large-scale medical imaging datasets and AI-driven inference systems.

Overview

MIST: Medical Imaging Streaming Toolkit

• Challenge: Large-scale imaging datasets require significant storage and bandwidth, limiting accessibility for AI research and clinical deployment.
• MIST Solution: A format-agnostic database enabling streaming of medical images at multiple resolutions and formats from a single high-resolution copy.
• Evaluation: Tested across eight diverse datasets (CT, MRI, X-ray) covering multiple modalities and file formats.
• Results: Reduced storage and bandwidth requirements without impacting image quality or downstream deep learning performance.
• Impact: Creates a data-efficient, format-agnostic platform that reduces barriers to AI research in medical imaging.

ISLE: Intelligent Streaming for AI Inference

• Motivation: Growing adoption of AI systems in radiology is increasing demands for bandwidth and computational resources.
• ISLE Framework: An intelligent streaming method inspired by video-on-demand platforms to deliver only the resolution needed for AI inference using progressive encoding.
• Results (Classification): Reduced transmission by ≥90% and decoding time by ≥87%
• Results (Segmentation): Reduced transmission by ≥77% and decoding time by ≥89%
• Performance: No impact on diagnostic performance (all P > 0.05).
• Impact: Improves data and computational efficiency for AI deployment in clinical environments without compromising diagnostic accuracy.

Open-Source Tools

Patents

Patent: WO2024233969A1 — Systems and methods for high-throughput analysis for graphical data

Filed by: University of Maryland Baltimore
Inventors: Vishwa S. Parekh, Pranav Kulkarni, Adway Kanhere, Paul H. Yi, Eliot L. Siegel

Publications

Kulkarni P., Kanhere A., Siegel E.L., Yi P.H., Parekh V.S. ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging. Journal of Imaging Informatics in Medicine. 2024 Dec;37(6):3250-63. DOI