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GTC ON-DEMAND

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Abstract:
Craig Morioka, UCLA Adjunct Associate Professor of Radiological Sciences, and Dima Lituiev, Postdoctoral Scholar at the University of California San Francisco, Institute for Computational Health Sciences, will discuss how they empower their fellow faculty, staff, and students with the latest techniques in training and deploying deep neural networks through NVIDIAs Deep Learning Institute (DLI) University Ambassador Program - a new AI and Deep Learning education enablement program for universities. This will include a dive into the benefits of an online learning platform, which uses GPUs in the cloud, by stepping through the DLIs online Image Segmentation and Radiomics labs. The Image Segmentation lab leverages an example from medical image analysis where it is often important to separate pixels corresponding to different types of tissue or cells for the purposes of diagnostics and treatment planning. Dima uses image segmentation in his research to facilitate diagnostics of kidney rejection by analyzing histological slides from patients with kidney transplants. We will explore how the Tensorflow code is structured and how the Tensorboard tool can be used to visualize structure and training dynamics of segmentation models. The focus of the Radiomics lab is detection of the 1p19q co-deletion biomarker using deep learning - specifically convolutional neural networks using the Keras and TensorFlow computing frameworks. Attendees will also learn how they can apply to become a DLI University Ambassador and bring the latest in Deep Learning and AI education to their academic communities.  
Craig Morioka, UCLA Adjunct Associate Professor of Radiological Sciences, and Dima Lituiev, Postdoctoral Scholar at the University of California San Francisco, Institute for Computational Health Sciences, will discuss how they empower their fellow faculty, staff, and students with the latest techniques in training and deploying deep neural networks through NVIDIAs Deep Learning Institute (DLI) University Ambassador Program - a new AI and Deep Learning education enablement program for universities. This will include a dive into the benefits of an online learning platform, which uses GPUs in the cloud, by stepping through the DLIs online Image Segmentation and Radiomics labs. The Image Segmentation lab leverages an example from medical image analysis where it is often important to separate pixels corresponding to different types of tissue or cells for the purposes of diagnostics and treatment planning. Dima uses image segmentation in his research to facilitate diagnostics of kidney rejection by analyzing histological slides from patients with kidney transplants. We will explore how the Tensorflow code is structured and how the Tensorboard tool can be used to visualize structure and training dynamics of segmentation models. The focus of the Radiomics lab is detection of the 1p19q co-deletion biomarker using deep learning - specifically convolutional neural networks using the Keras and TensorFlow computing frameworks. Attendees will also learn how they can apply to become a DLI University Ambassador and bring the latest in Deep Learning and AI education to their academic communities.    Back
 
Topics:
AI Application Deployment and Inference, Deep Learning and AI Frameworks, AI and DL Business Track (high level)
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8823
Streaming:
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