Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5
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Hai VU, Tomio ECHIGO, Ryusuke SAGAWA, Keiko YAGI, Masatsugu SHIBA, Kazuhide HIGUCHI, Tetsuo ARAKAWA, Yasushi YAGI, "Controlling the Display of Capsule Endoscopy Video for Diagnostic Assistance" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 3, pp. 512-528, March 2009, doi: 10.1587/transinf.E92.D.512.
Abstract: Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.512/_p
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@ARTICLE{e92-d_3_512,
author={Hai VU, Tomio ECHIGO, Ryusuke SAGAWA, Keiko YAGI, Masatsugu SHIBA, Kazuhide HIGUCHI, Tetsuo ARAKAWA, Yasushi YAGI, },
journal={IEICE TRANSACTIONS on Information},
title={Controlling the Display of Capsule Endoscopy Video for Diagnostic Assistance},
year={2009},
volume={E92-D},
number={3},
pages={512-528},
abstract={Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5
keywords={},
doi={10.1587/transinf.E92.D.512},
ISSN={1745-1361},
month={March},}
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TY - JOUR
TI - Controlling the Display of Capsule Endoscopy Video for Diagnostic Assistance
T2 - IEICE TRANSACTIONS on Information
SP - 512
EP - 528
AU - Hai VU
AU - Tomio ECHIGO
AU - Ryusuke SAGAWA
AU - Keiko YAGI
AU - Masatsugu SHIBA
AU - Kazuhide HIGUCHI
AU - Tetsuo ARAKAWA
AU - Yasushi YAGI
PY - 2009
DO - 10.1587/transinf.E92.D.512
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2009
AB - Interpretations by physicians of capsule endoscopy image sequences captured over periods of 7-8 hours usually require 45 to 120 minutes of extreme concentration. This paper describes a novel method to reduce diagnostic time by automatically controlling the display frame rate. Unlike existing techniques, this method displays original images with no skipping of frames. The sequence can be played at a high frame rate in stable regions to save time. Then, in regions with rough changes, the speed is decreased to more conveniently ascertain suspicious findings. To realize such a system, cue information about the disparity of consecutive frames, including color similarity and motion displacements is extracted. A decision tree utilizes these features to classify the states of the image acquisitions. For each classified state, the delay time between frames is calculated by parametric functions. A scheme selecting the optimal parameters set determined from assessments by physicians is deployed. Experiments involved clinical evaluations to investigate the effectiveness of this method compared to a standard-view using an existing system. Results from logged action based analysis show that compared with an existing system the proposed method reduced diagnostic time to around 32.5
ER -