Rudolph Pienaar, Dr. Eng

 

Technical Director
Fetal-Neonatal Neuroimaging and Developmental Science Center


Staff Scientist
Boston Children's Hospital
 


overview

  • background
  • experience
  • research and development
  • projects

introduction

Technical Director

Lead software design efforts at improving computational research

  • Software/cloud compute
  • Portability of computation and data
  • Algorithmic design 

background

PhD Electrical/Electronic Engineering

  • Reinforcement Learning in biomechanical control system (self adapting posture balancer)

 

PostDoc

  • MRI processing                                                                     
    • Some pre-processing
    • Mostly post-processing

Faculty

  • Imaging research
  • Software system development

 


experience

15+ years in medical software R&D

  • Image pre-processing
    • Pulse Programming on Siemens MRI scanners
    • Software for off-line rapid k-space inverse FFT
  • Image post-processing
    • DICOM data structures
    • Mathematical analysis of reconstructed brain surfaces
  • Systems architecture
    • Pipeline design
    • Visualization on the web
    • Remote computation using containerization

experience (team)

  • 10+ years experience in team leading
    • Lead several small, agile software teams
    • Project development cycle in 6 month periods
  • Web-based visualization
    • xtk
    • ami
  • Remote computation/coordination
    • CHRIS 

experience (team)

  • 5+ years in industry/academia collaborative projects
    • Cloud-based radiology
      • Massachusetts Open Cloud
    • GE Healthcare/cloud
      • Image data to/from GE cloud
      • Normative image comparison
    • NVidia
      • ​​Academic research partner
        • Hardware support for in-house cluster

experience (team)

5+ years in industry/acadmia collaborative projects

  • GE
    • Learning factory
    • Coolidge.io
  • IBM
    • Partner with PowerAI tools and evaluation
    • IBM Watson
    • Nimbix Advanced HPC
  • RedHat
    • Lead developer with cloud-based scheduling and computation on open cloud

research and development

Lead Architect for software system development

  • medical computational environments
  • understanding data needs and constraints
  • understanding computational requirements for medical settings
    • clinical
    • research
  • Design systems to interface with home-grown AI pipelines
  • Design systems to interface with industry
    standard AI tools and pipelines

research and development

Design systems to interface with compute agnostic pipelines:

  • Allow for rapid deployment of computational tools
    • Use best tool for problem
  • Standardized development process
  • Web-based, cloud-based
  • All data handled by system
  • Powerful visualization libraries for input and
    output data

research and development

Design systems to interface with AI pipelines:

  • Predictive algorithms
  • NIRS related ML and data mining
  • Monte Carlo simulations of light propagation through brain tissue leveraging GPUs
  • Prostate nerve image segmentation with University of Magdeburg using U-NN

research and development

  • Design systems to interface with industry standard tools:
    • Python-based tool chain and environment
    • Use available and established data-science frameworks:
      • tensorflow
      • keras
      • opencv-python
      • pandas
      • scikit-image
      • etc

research and development

  • GE Healthcare:
    • Visualization for Radiology Workbench
    • Interface with GE cloud for data storage
    • Interface with GE AI tools:
      • Learning Factory
      • Route 66
      • Coolidge
        ​

On going and deepening collaboration for systems development.


research and development

  • Nvidia:
    • Tensor-flow libraries
    • Nvidia openlabs

 

Use of lower-level tools and libraries for specific neural-network training in image analysis tasks.


research and development

  • IBM:
    • PowerAI systems and software
      • Collaboration on the Massachusetts Open Cloud
         

Use IBM available AI tools for object / scene recognition and develop framework to connect to medical data.


research and development

  • RedHat, Inc:
    • Collaboration on the Massachusetts Open Cloud
    • Openstack / kubernetes
    • Openswift


Develop backend opensource infrastructure to use framework on industry standard cloud systems.


medical compute... in the cloud

definite need for data mobility and centralization...

with compute being "free" to process data where-ever it might naturally collect...


CHRIS...

CHRIS is a bio-medical data workflow manage that allows easy and intuitive collection, analysis, and sharing of data between parties.

  • allows for advanced view rendering
  • allows for sharing of images
  • allows for immersive real time collaboration
  • allows for post-processing of images

many data sources... many compute sources...

via here

connect data here

to here...

and compute!


overview / goals

how do I run this on the cloud?

how do I run this on "someone else's computer"?


system topology

Main web server local data repository

remote compute nodes

data source (e.g. in hospital PACS)


UI concepts


UI concepts


UI concepts


Research and Development

  • Novel platforms for connecting data to compute
  • Develop and deploy systems with rapid turnover (6 - 9 month development cycle)
  • Connect advanced imaging from cloud to bedside
  • Build community around software development
  • Considerable experience connecting leading research institutes with leading industry partners

 


University partnerships

Boston area computer science and engineering 

Mentoring students on Cloud computing

Academic partner on the Massachusetts Open Cloud -- largest "open" cloud for general computation in the US


RedHat partnership

RedHat is active partner developing CHRIS infrastructure to the MOC

CHRIS as platform to help foster community and opensource development in the cloud using this paradigm

RedHat interested in helping use CHRIS to be a platform for "hack-a-thons" based on openswift, kubernetes, etc.


DL partnerships

GE Healthcare and cloud computing and GE deep learning products

IBM high performance computation and access to underlying engines/libraries

NVidia openlabs


MOC


references... ChRIS

  • https://github.com/FNNDSC/ChRIS_ultron_backEnd
  • https://github.com/FNNDSC/ChRIS_ultron_frontEnd

references... services

 
  • https://github.com/FNNDSC/viewerjs
  • https://github.com/FNNDSC/gcjs
  • https://github.com/FNNDSC/fmjs
  • https://github.com/FNNDSC/toolbarjs
  • https://github.com/FNNDSC/rboxjs
  • https://github.com/FNNDSC/rendererjs
  • https://github.com/FNNDSC/thbarjs
  • https://github.com/FNNDSC/pman
  • https://github.com/FNNDSC/pfioh
  • https://github.com/FNNDSC/pfcon

references... viewers

  • https://goxtk.com

  • https://github.com/FNNDSC/ami

team

  • Jorge Bernal
  • Nicolas Rannou
  • Rudolph  Pienaar
  • Yangming Ou
  • Daniel Haehn
  • Daniel Ginsburg
  • Ellen Grant

BCH Team

BU Team

  • Orran Krieger
  • Ata Turk
  • Aditya Awalker

RedHat

  • Dan McPherson
  • and others!

fin!

Thank you!

self_overview_yitu

By Rudolph Pienaar

self_overview_yitu

Quick intro / overview

  • 1,024

More from Rudolph Pienaar