2017 Winter Project Week/Deep Learning for Medical Image Computation

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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
  • Deep Learning hands-on tutorial: Image segmentation lab with TensorFlow (Abel Brown, Abdul Alhalabi) (Monday 3-5pm)
  • Deep Learning hands-on tutorial: Electronic health records lab with Keras (Abel Brown, Abdul Alhalabi) (Monday 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)
  • All sessions were well attended (30-100 attendees). Specific feedback: google tensorflow tutorial should have been the first one in the series
  • MGH Center for Clinical Data Science presented and loaned high performance machines for the week
  • Successful use of prostate segmentation code across multiple institutions

Background and References