scholarly journals [Paper] Quality Improvement for Real-time Free Viewpoint Video Using View-dependent Shape Refinement

2021 ◽  
Vol 9 (4) ◽  
pp. 247-261
Author(s):  
Ryosuke Watanabe ◽  
Tomoaki Konno ◽  
Keisuke Nonaka ◽  
Tatsuya Kobayashi ◽  
Haruhisa Kato ◽  
...  
Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Adam Prater ◽  
Meredith Bowen ◽  
Emily Pavich ◽  
Thomas Loehfelm ◽  
Aaron M Anderson ◽  
...  

Background: Real-Time Location Systems (RTLS) utilize tracking tags and detectors to locate objects or people. This technology has been implemented in healthcare, chiefly to track hospital assets, and a few healthcare systems have applied this technology to track patients in the emergency department. This pilot study tested the feasibility of RTLS to monitor the acute stroke workflow in a large, urban hospital. Methods: An asset tracking RTLS was installed in a large, urban hospital. A series of 21 acute stroke patients were tracked throughout the workflow process by a human observer and via RTLS asset tag attached to the patient’s hospital equipment. A Wi-Fi detector documented initial patient arrival times in the ER Hallway, radiofrequency/infrared (RFID/IR) detectors documented ER CT scanner and ER patient room times. Patient Arrival and departure times in the emergency room (ER) and radiology CT scanner were measured. Time differences between human observer and RTLS were calculated. Results: A total of 21 patients were tracked with RTLS. The mean time difference, interquartile range and standard deviation in minutes are as follows: initial arrival (mean 106, IQR 112, SD 197); CT arrival ( mean 1, IQR 1, SD 0.86); CT departure (mean 2, IQR 2, SD 1.13); patient return to ED (mean 1, IQR 1, SD 0.94). Discussion: Our data demonstrate that RTLS can provide accurate, real-time patient location information, and has the potential to provide data for quality improvement. Combination RFID/IR detectors provided accurate time information while the Wi-Fi detector, proved unreliable for initial arrival times. Our preliminary data supports the development of an unique RTLS system specifically designed to allow for complete visualization of the stroke workflow from patient arrival to treatment along with a dashboard user interface to facilitate treatment team coordination.


Author(s):  
James L. Wofford ◽  
James R. Kimberly ◽  
William P. Moran ◽  
David P. Miller ◽  
Jerry L. Hopping ◽  
...  

2015 ◽  
Vol 24 (4) ◽  
pp. 272-281 ◽  
Author(s):  
Brian M Wong ◽  
Sonia Dyal ◽  
Edward E Etchells ◽  
Sandra Knowles ◽  
Lauren Gerard ◽  
...  

2007 ◽  
Vol 204 (4) ◽  
pp. 527-532 ◽  
Author(s):  
Terry Altpeter ◽  
Kitty Luckhardt ◽  
John N. Lewis ◽  
Alden H. Harken ◽  
Hiram C. Polk

2015 ◽  
Vol 3 (1) ◽  
pp. e13 ◽  
Author(s):  
James Lucius Wofford ◽  
Claudia L Campos ◽  
Robert E Jones ◽  
Sheila F Stevens

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