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Ultrasound Scanner 27 September 2017 By Erik N. Steen, Chief - PowerPoint PPT Presentation

Session 23440 The Intelligent Cardiovascular Ultrasound Scanner 27 September 2017 By Erik N. Steen, Chief Engineer GEHC Cardiovascular Ultrasound This presentation partly describes ongoing research and development efforts. These efforts are not


  1. Session 23440 The Intelligent Cardiovascular Ultrasound Scanner 27 September 2017 By Erik N. Steen, Chief Engineer GEHC Cardiovascular Ultrasound This presentation partly describes ongoing research and development efforts. These efforts are not products and may never become products JB52083XX Vivid is a trademark of General Electric Company.

  2. Cardiologist How can I be confident in my ability to manage my patient’s heart health when 10-15% of the patients have suboptimal echoes? Interventional Cardiologist I need a better understanding of the anatomy and function during structural heart repairs

  3. Vivid ™ E95 Cardiovascular Ultrasound with Vivid and cSound are trademarks of General Electric Company.

  4. cSound Intelligent processing • Channel data from many transmits collected into GPU memory in real time • Image is computed in real time by software algorithms • High performance • Great flexibility to change algorithms 4

  5. HD live ™ Ex Exam amples les from om in interventi ventions ons Vivid, cSound, HD live are trademarks of General Electric company or one of it’s subsidiaries.

  6. With cSound ™ , image reconstruction algorithms can be changed according to clinical needs Texture Amyloidosis example (ACE+TCI vs vs Texture)

  7. Blood flow can be visualized in completely new ways

  8. Cardiologist How can I be confident in my ability to manage my patient’s heart health when 10-15% of the patients have suboptimal echoes? I need a better understanding of the anatomy and function during structural heart repairs How can I become more efficient with the increased burden of cardiovascular disease and pressure on cost ?

  9. Automatic Doppler Measurements Performing manual Doppler measurements (tracings) is time consuming Active for the most common measurements: LVOT Vmax LVOT Trace AV Vmax AV Trace TR Vmax MV E/A Velocity E’ Auto Doppler may reduce scan time , improve consistency (less user dependent) and eventually make the exam more efficient 9

  10. Cardiologist How can I be confident in my ability to manage my patient’s heart health when 10-15% of the patients have suboptimal echoes? I need a better understanding of the anatomy and function during structural heart repairs How can I become more efficient with the increased burden of cardiovascular disease and pressure on cost ? How can I make sure my cardiovascular ultrasound system is future-proof ?

  11. Future development(*) *Note: Technology in development that represents ongoing research and development efforts. These technologies are not products and may never become products. Not for sale. Not cleared or approved by the U.S. FDA or any other global regulator for commercial availability JB52083XX Vivid is a trademark of General Electric Company.

  12. Faster GPUs can be combined with new algorithms for greatly improved 3D imaging (*) *Note: Technology in development that represents ongoing research and development efforts. These technologies are not products and may never become 12 products. Not for sale. Not cleared or approved by the U.S. FDA or any other global regulator for commercial availability

  13. cSound Intelligent workflow • Workflow is automatically optimized according to cardiac view. *Note: Technology in development that represents ongoing research and development efforts. These technologies are not products and may never become 13 products. Not for sale. Not cleared or approved by the U.S. FDA or any other global regulator for commercial availability

  14. Automatic Cardiac View Recognition (*) Apical 4 chamber view Apical 2 chamber view Apical long axis view Parasternal long axis view Parasternal short axis view Preliminary results • Data: >100.000 images from > 5000 loops with variable image quality & patient anatomy • 500 loops used for validation • Various network architectures investigated • Accuracy (CaffeNet): 96 % accuracy on frame level, 97 % accuracy on sequence level (using majority vote) • < 2 ms per frame inference time using a Quadro P4000 GPU *Note: Technology in development that represents ongoing research and development efforts. These technologies are not products and may never become products. Not for sale. Not cleared or approved by the U.S. FDA or any other global regulator for commercial availability 14

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