WEBINAR
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Date: July 22, 2021
Time: 09:00am – 10:00am PT
Duration: 1 hour
Time: 09:00am – 10:00am PT
Duration: 1 hour
Image segmentation deals with placing each pixel (or voxel in the case of 3D) of an image into specific classes that share common characteristics. In medical imaging, image segmentation can be used to help identify organs and anomalies, measure them, classify them, and even uncover diagnostic information by using data gathered from x-rays, magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and more. However, building, training, and optimizing an accurate image segmentation AI model from scratch can be time consuming for novices and experts alike.
By attending this webinar, you will learn:
- How NVIDIA NGC™ and NVIDIA Clara™ (NVIDIA’s healthcare AI Platform) can help accelerate medical imaging workflows
- How to use a sample Jupyter notebook with a pretrained image segmentation model from the NGC catalog
- How to refine the model by retraining it using your own hyperparameters and test it using your own checkpoints
- Where to go for next steps, including MONAI and NVIDIA Clara Imaging
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DGX Station Whitepaper
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Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speakers
Akhil Docca
Senior Product Marketing Manager, NGC, NVIDIAAkhil Docca is a senior product marketing manager for NGC at NVIDIA, focusing in HPC and DL containers. Akhil has a Master’s in Business Administration from UCLA Anderson School of Business and a Bachelor’s degree in Mechanical Engineering from San Jose State University.
Shokoufeh Monjezi Kouchak
Technical Marketing Engineer, NVIDIAShokoufeh is a technical marketing engineer at NVIDIA, focusing on deep learning models. Shokoufeh obtained her Phd degree in computer engineering from Arizona State University, where she focused on driver behavior analysis and driver distraction detection with deep learning models.
Vanessa Braunstein
Product Marketing for Clara, Healthcare, NVIDIAVanessa Braunstein leads product marketing for NVIDIA Healthcare. Previously, she was in strategy, product development and marketing for genomics, medical imaging, pharmaceutical, and clinical diagnostic companies. She received her BA from UC Berkeley in molecular and cell biology, and then studied public health and business at UCSF and UCLA. She has worked with life science researchers and the clinical community for the last few years on building and implementing AI to optimize workflows in hospitals, medical research institutions, pharmaceutical companies, and cancer centers
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