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GTC ON-DEMAND

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Abstract:
We'll present our experience in the development of a multidisciplinary project for the early detection of pancreatic cancer. We'll present the FELIX project goals and the challenges including how we defined our goals and collected over 1300 annotated CT datasets for developing and testing deep learning algorithms. We will describe the deep network that we are using and discuss our results and future directions. This type of research has great potential for developing assistive devices for Radiologists as a second reader, high quality annotated datasets are critical for making progress in this field and are time consuming and expensive to acquire. This type of research is performed best by teams that combine expertise in Radiology and Machine Learning.
We'll present our experience in the development of a multidisciplinary project for the early detection of pancreatic cancer. We'll present the FELIX project goals and the challenges including how we defined our goals and collected over 1300 annotated CT datasets for developing and testing deep learning algorithms. We will describe the deep network that we are using and discuss our results and future directions. This type of research has great potential for developing assistive devices for Radiologists as a second reader, high quality annotated datasets are critical for making progress in this field and are time consuming and expensive to acquire. This type of research is performed best by teams that combine expertise in Radiology and Machine Learning.  Back
 
Topics:
AI in Healthcare
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7266
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