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ITK, 3D Slicer, and MONAI:
Creating and sustaining impact
with open science
Stephen R. Aylward, Ph.D.
Chair of MONAI Advisory Board
Senior Director of Strategic Initiatives, Kitware
What is open science?
“Reproducible Science”
Writing open-source code,
sharing data, and
sharing publications
so that others can fully replicate your work…
“DOUBT EVERYTHING and only believe
in those things that are evidently true
(reproducible)”
-- Descartes 1637
Discourse on the (Scientific) Method
“Open Science” began in 17th century with
the advent of the academic journal
Outline
⬣ ITK: Mainstream open science for medical imaging
⬣ 3D Slicer: Accelerating clinical translation
⬣ MONAI: The best of open science and beyond
The Insight Toolkit (ITK): Open source since 1999
⬣ 1999: “I can do it better on my own…”
⬣ ITK 1999-2005
● $13.5M (NIH + 6 teams)
⬣ ITK 2023
● 41,085 commits
● 302 contributors
● 1,253,083 lines of code
● C++ and Python
● DICOM and 40 other image formats
● Image Segmentation
● Image Registration
● GPU Acceleration, Distributed Processing
● Pathology / microscopy (massive image) support
● Integrated into BioImage Suite, Osirix, MeVisLab, 3D Slicer, MONAI, …
The Insight Toolkit
⬣ Mainstream Open Science
for Medical Imaging = Insight Journal, 2006
● ITK contribution = Insight Journal publication
⚬ PDF
⚬ Code
⚬ Data
● 1,900+ publications
● 360,000+ downloads
● DOI for citations
● Continuous testing
● Apache 2.0: Commercial use allowed!
⚬ Rigorous evaluation and bug fixing
● Open Science -> ITK Growth and Stability -> 3D Slicer (and others)
3D Slicer
⬣ Graphical User Interface to ITK (and other TKs)
⬣ Advanced visualizations
⬣ Analysis of medical, biomedical, and other 3D images and meshes
⬣ Planning and navigating image-guided procedures
⬣ Customized into regulatory approved, commercial applications (commercial
use)
⬣ Vehicle for the development and delivery of AI (MONAI)…
Why is deep learning (AI) succeeding?
1. Performance
2. Open Science
-- Forbes.com
Deep Learning Success: MONAI Performance
⬣ Endoscopy Tool Segmentation
Deep Learning Success: Open Science
Open science is pervasive in deep learning
⬣ Open access publications: arXiv
⬣ Open access data: TCIA (IDC), ImageNet, DICOM, FIHR
● License = CC By (not CC NC)
⬣ Open access software: PyTorch, MONAI
● License = Apache 2.0
Medical Open Network for A. I. (MONAI)
Goal: Accelerate the pace of research and development by
providing a common software foundation and
a vibrant community for medical imaging deep learning.
■ Began as a collaboration between Nvidia and King’s College London
■ Prerna Dogra (NVidia) and Jorge Cardoso (KCL)
■ Freely available and community-supported
■ PyTorch-based
■ Optimized for medical imaging
■ Prioritizes reproducibility
MONAI is…
Impacting the entire imaging workflow…
12
12
MONAI is…
Image Reconstruction
13
13
MONAI is
Image Segmentation
14
14
• Transformers
• Contrastive learning
• Auto3DSeg
• nn-UNet
• …
MONAI is…
Longitudinal studies
15
15
MONAI is…
Survival Prediction
16
16
1.1M+ Downloads
150+ Individual contributors
3,400+ Gihub stars
480+ Derived projects
600+ Google Scholar results from
‘ “MONAI” medical deep learning ’
MONAI is…
MONAI 1.0 (Sept. 2022)
MONAI 1.0 (Sept. 2022)
MONAI + Hardware (MONAI Stream)
⬣ Holoscan SDK
● AI interfaced with hardware
● CPU or accelerated on an Nvidia GPU
● Low latency
● Parallel inference (multiple AI models running simultaneously)
● Ultrasound devices, ROS[2], DaVinci (DVRK), Frame grabbers, GPUs, AR/VR, …
● Holoscan-approved hardware provides a pathway to regulatory approval…
Jetson, Nano, AGX, …
What’s needed for even broader impact from open science?
⬣ Regulatory approval that confirms the safety of community-supported,
open-source software, without commercial sales or individual
(developer) liability.
● Transparent process
● Continuous testing
● World-wide use
21
21
ITK, 3D Slicer, and MONAI:
Creating and sustaining impact
with open science
Stephen R. Aylward, Ph.D.
Chair of MONAI Advisory Board
Senior Director of Strategic Initiatives, Kitware
Thank you!

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ITK, 3D Slicer, MONAI: Creating and sustaining impact with open science

  • 1. ITK, 3D Slicer, and MONAI: Creating and sustaining impact with open science Stephen R. Aylward, Ph.D. Chair of MONAI Advisory Board Senior Director of Strategic Initiatives, Kitware
  • 2. What is open science? “Reproducible Science” Writing open-source code, sharing data, and sharing publications so that others can fully replicate your work…
  • 3. “DOUBT EVERYTHING and only believe in those things that are evidently true (reproducible)” -- Descartes 1637 Discourse on the (Scientific) Method “Open Science” began in 17th century with the advent of the academic journal
  • 4. Outline ⬣ ITK: Mainstream open science for medical imaging ⬣ 3D Slicer: Accelerating clinical translation ⬣ MONAI: The best of open science and beyond
  • 5. The Insight Toolkit (ITK): Open source since 1999 ⬣ 1999: “I can do it better on my own…” ⬣ ITK 1999-2005 ● $13.5M (NIH + 6 teams) ⬣ ITK 2023 ● 41,085 commits ● 302 contributors ● 1,253,083 lines of code ● C++ and Python ● DICOM and 40 other image formats ● Image Segmentation ● Image Registration ● GPU Acceleration, Distributed Processing ● Pathology / microscopy (massive image) support ● Integrated into BioImage Suite, Osirix, MeVisLab, 3D Slicer, MONAI, …
  • 6. The Insight Toolkit ⬣ Mainstream Open Science for Medical Imaging = Insight Journal, 2006 ● ITK contribution = Insight Journal publication ⚬ PDF ⚬ Code ⚬ Data ● 1,900+ publications ● 360,000+ downloads ● DOI for citations ● Continuous testing ● Apache 2.0: Commercial use allowed! ⚬ Rigorous evaluation and bug fixing ● Open Science -> ITK Growth and Stability -> 3D Slicer (and others)
  • 7. 3D Slicer ⬣ Graphical User Interface to ITK (and other TKs) ⬣ Advanced visualizations ⬣ Analysis of medical, biomedical, and other 3D images and meshes ⬣ Planning and navigating image-guided procedures ⬣ Customized into regulatory approved, commercial applications (commercial use) ⬣ Vehicle for the development and delivery of AI (MONAI)…
  • 8. Why is deep learning (AI) succeeding? 1. Performance 2. Open Science -- Forbes.com
  • 9. Deep Learning Success: MONAI Performance ⬣ Endoscopy Tool Segmentation
  • 10. Deep Learning Success: Open Science Open science is pervasive in deep learning ⬣ Open access publications: arXiv ⬣ Open access data: TCIA (IDC), ImageNet, DICOM, FIHR ● License = CC By (not CC NC) ⬣ Open access software: PyTorch, MONAI ● License = Apache 2.0
  • 11. Medical Open Network for A. I. (MONAI) Goal: Accelerate the pace of research and development by providing a common software foundation and a vibrant community for medical imaging deep learning. ■ Began as a collaboration between Nvidia and King’s College London ■ Prerna Dogra (NVidia) and Jorge Cardoso (KCL) ■ Freely available and community-supported ■ PyTorch-based ■ Optimized for medical imaging ■ Prioritizes reproducibility
  • 12. MONAI is… Impacting the entire imaging workflow… 12 12
  • 14. MONAI is Image Segmentation 14 14 • Transformers • Contrastive learning • Auto3DSeg • nn-UNet • …
  • 17. 1.1M+ Downloads 150+ Individual contributors 3,400+ Gihub stars 480+ Derived projects 600+ Google Scholar results from ‘ “MONAI” medical deep learning ’ MONAI is…
  • 20. MONAI + Hardware (MONAI Stream) ⬣ Holoscan SDK ● AI interfaced with hardware ● CPU or accelerated on an Nvidia GPU ● Low latency ● Parallel inference (multiple AI models running simultaneously) ● Ultrasound devices, ROS[2], DaVinci (DVRK), Frame grabbers, GPUs, AR/VR, … ● Holoscan-approved hardware provides a pathway to regulatory approval… Jetson, Nano, AGX, …
  • 21. What’s needed for even broader impact from open science? ⬣ Regulatory approval that confirms the safety of community-supported, open-source software, without commercial sales or individual (developer) liability. ● Transparent process ● Continuous testing ● World-wide use 21 21
  • 22. ITK, 3D Slicer, and MONAI: Creating and sustaining impact with open science Stephen R. Aylward, Ph.D. Chair of MONAI Advisory Board Senior Director of Strategic Initiatives, Kitware Thank you!