The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Tafsiran oleh pakar perubatan bagi jujukan imej endoskopi kapsul yang ditangkap dalam tempoh 7-8 jam biasanya memerlukan 45 hingga 120 minit kepekatan melampau. Makalah ini menerangkan kaedah baru untuk mengurangkan masa diagnostik dengan mengawal kadar bingkai paparan secara automatik. Tidak seperti teknik sedia ada, kaedah ini memaparkan imej asal tanpa melangkau bingkai. Urutan boleh dimainkan pada kadar bingkai yang tinggi di kawasan yang stabil untuk menjimatkan masa. Kemudian, di kawasan yang mengalami perubahan kasar, kelajuan dikurangkan untuk memastikan penemuan yang mencurigakan dengan lebih mudah. Untuk merealisasikan sistem sedemikian, maklumat isyarat tentang ketaksamaan bingkai berturut-turut, termasuk persamaan warna dan anjakan gerakan diekstrak. Pepohon keputusan menggunakan ciri ini untuk mengklasifikasikan keadaan pemerolehan imej. Bagi setiap keadaan terperingkat, masa tunda antara bingkai dikira oleh fungsi parametrik. Skim memilih set parameter optimum yang ditentukan daripada penilaian oleh pakar perubatan digunakan. Eksperimen melibatkan penilaian klinikal untuk menyiasat keberkesanan kaedah ini berbanding paparan standard menggunakan sistem sedia ada. Keputusan daripada analisis berasaskan tindakan log menunjukkan bahawa berbanding dengan sistem sedia ada kaedah yang dicadangkan mengurangkan masa diagnostik kepada sekitar 32.5
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Salinan
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
Salinan
@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},}
Salinan
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 -