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GTC ON-DEMAND

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Abstract:
Radiological assessment and quantification of liver lesions currently relies on measurements of longest linear diameter to quantify size, which is a misleading way to measure irregularly shaped lesions. Volumetric assessment, on the other hand, gives a much better impression of overall lesion size. One of the greatest roadblocks to calculating lesion volume is the amount of time it takes to demarcate the boundaries of an individual lesion. Arterys is working on empowering the radiologist with an automated method for volumetric assessment of liver lesions. This automated method is built using a convolutional network. When integrated into Arterys web platform, it enables volumetric assessment with a single mouse click.
Radiological assessment and quantification of liver lesions currently relies on measurements of longest linear diameter to quantify size, which is a misleading way to measure irregularly shaped lesions. Volumetric assessment, on the other hand, gives a much better impression of overall lesion size. One of the greatest roadblocks to calculating lesion volume is the amount of time it takes to demarcate the boundaries of an individual lesion. Arterys is working on empowering the radiologist with an automated method for volumetric assessment of liver lesions. This automated method is built using a convolutional network. When integrated into Arterys web platform, it enables volumetric assessment with a single mouse click.  Back
 
Topics:
Medical Imaging & Radiology, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9272
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Abstract:

Radiological diagnosis and interpretation should not take place in a vacuum -- but today, it does. One of the greatest challenges the radiologist faces when interpreting studies is understanding the individual patient in the context of the millions of patients who have come previously. Without access to historical data, radiologists must make clinical decisions based only on their memory of recent cases and literature. Arterys is working to empower the radiologist with an intelligent lung nodule reference library that automatically retrieves historical cases that are relevant to the current case. The intelligent lung nodule reference library is built on top of our state-of-the-art deep learning-based lung nodule detection, segmentation and characterization system.

Radiological diagnosis and interpretation should not take place in a vacuum -- but today, it does. One of the greatest challenges the radiologist faces when interpreting studies is understanding the individual patient in the context of the millions of patients who have come previously. Without access to historical data, radiologists must make clinical decisions based only on their memory of recent cases and literature. Arterys is working to empower the radiologist with an intelligent lung nodule reference library that automatically retrieves historical cases that are relevant to the current case. The intelligent lung nodule reference library is built on top of our state-of-the-art deep learning-based lung nodule detection, segmentation and characterization system.

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Topics:
AI in Healthcare, Medical Imaging & Radiology
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8507
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Abstract:
Sad but true: most of radiology is mind-numbing tedium. Radiologists spend countless hours on tasks that are onerous and error-prone, resulting in high costs and frequent misdiagnoses. Our first product designed to address these deficiencies is Arterys Cardio DL, a web-based, zero-footprint cardiac MRI postprocessing suite. Arterys Cardio DL includes a deep learning-based contouring algorithm that vastly reduces the time required to diagnose heart disease in cardiac MRI. Arterys Cardio DL is the first technology ever to be cleared by the FDA that leverages cloud computing and deep learning in a clinical setting. We'll discuss the technology behind the software and how we proved its safety and efficacy to secure FDA clearance in the United States and the CE Mark in Europe.
Sad but true: most of radiology is mind-numbing tedium. Radiologists spend countless hours on tasks that are onerous and error-prone, resulting in high costs and frequent misdiagnoses. Our first product designed to address these deficiencies is Arterys Cardio DL, a web-based, zero-footprint cardiac MRI postprocessing suite. Arterys Cardio DL includes a deep learning-based contouring algorithm that vastly reduces the time required to diagnose heart disease in cardiac MRI. Arterys Cardio DL is the first technology ever to be cleared by the FDA that leverages cloud computing and deep learning in a clinical setting. We'll discuss the technology behind the software and how we proved its safety and efficacy to secure FDA clearance in the United States and the CE Mark in Europe.  Back
 
Topics:
Artificial Intelligence and Deep Learning, AI Startup, Healthcare and Life Sciences, AI in Healthcare, Medical Imaging & Radiology
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7654
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