2017 Winter Project Week/Deep Learning for Medical Image Computation

From NAMIC Wiki
Jump to: navigation, search
Home < 2017 Winter Project Week < Deep Learning for Medical Image Computation

Key Investigators

  • Tina Kapur, BWH/HMS
  • Steve Pieper, Isomics
  • Abdul Al Halabi, nVIDIA
  • Abel Brown, nVIDIA
  • Joshua Moore, MGH Clinical Data Science Center
  • Mohsen Ghafoorian, Radboud University
  • Luis Ibanez, Google
  • Alireza Mehrtash, UBC/BWH

Project Description

Objective Approach and Plan Progress and Next Steps
  • To provide an introduction to proven concepts from Deep Learning that are making high impact in medical image computation.
  • 11 Projects that plan to use/investigate Deep Learning on Medical Images + clinical data
  • Hands-on Tutorial on using GPUs for Deep Learning (Abel Brown, Abdul Alhalabi) (Monday 3-5pm, 5:30-7pm)
  • Newly Launched MGH Clinical Data Science Center with focus on GPU and Machine Learning (Joshua Moore) (Monday 5-5:30pm)
  • Basic Concepts in Neural Network Methodology (Mohsen Ghafoorian) (Tuesday 1-3pm)
  • Tensorflow Workshop (Luis Ibanez) (Wednesday 10am-12pm)
  • Methodology Continued: Unet, Segmentation (Mohsen Ghafoorian) (Wednesday 3-3:45pm)
  • DeepInfer Extension Manager for an Open Source Repository for Deep Learning networks (Alireza Mehrtash) (Wednesday 3:45-4pm)

Background and References

Retrieved from "https://www.na-mic.org/w/index.php?title=2017_Winter_Project_Week/Deep_Learning_for_Medical_Image_Computation&oldid=94586"