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Assessment of experimental OpenCV tracking algorithms for ultrasound videos
This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neop...
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Published in: | Scientific reports 2023-04, Vol.13 (1), p.6765-6765, Article 6765 |
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creator | Levin, A. A. Klimov, D. D. Nechunaev, A. A. Prokhorenko, L. S. Mishchenkov, D. S. Nosova, A. G. Astakhov, D. A. Poduraev, Y. V. Panchenkov, D. N. |
description | This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms—CSRT and KCF—could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. So, the hypothesis for future work is combining these algorithms to work together, with one of them—CSRT—as support for the KCF tracker on the rarely failed frames. |
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A. ; Klimov, D. D. ; Nechunaev, A. A. ; Prokhorenko, L. S. ; Mishchenkov, D. S. ; Nosova, A. G. ; Astakhov, D. A. ; Poduraev, Y. V. ; Panchenkov, D. N.</creator><creatorcontrib>Levin, A. A. ; Klimov, D. D. ; Nechunaev, A. A. ; Prokhorenko, L. S. ; Mishchenkov, D. S. ; Nosova, A. G. ; Astakhov, D. A. ; Poduraev, Y. V. ; Panchenkov, D. N.</creatorcontrib><description>This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms—CSRT and KCF—could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. So, the hypothesis for future work is combining these algorithms to work together, with one of them—CSRT—as support for the KCF tracker on the rarely failed frames.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-023-30930-3</identifier><identifier>PMID: 37185281</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>639/166/985 ; 692/4028/546 ; Algorithms ; Biopsy ; Computer vision ; Computers ; Experiments ; Humanities and Social Sciences ; Humans ; Hypotheses ; Movement ; multidisciplinary ; Robotic surgery ; Robotic Surgical Procedures ; Science ; Science (multidisciplinary) ; Tumors ; Ultrasonic imaging ; Ultrasound</subject><ispartof>Scientific reports, 2023-04, Vol.13 (1), p.6765-6765, Article 6765</ispartof><rights>The Author(s) 2023</rights><rights>2023. The Author(s).</rights><rights>The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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A.</creatorcontrib><creatorcontrib>Klimov, D. D.</creatorcontrib><creatorcontrib>Nechunaev, A. A.</creatorcontrib><creatorcontrib>Prokhorenko, L. S.</creatorcontrib><creatorcontrib>Mishchenkov, D. S.</creatorcontrib><creatorcontrib>Nosova, A. G.</creatorcontrib><creatorcontrib>Astakhov, D. A.</creatorcontrib><creatorcontrib>Poduraev, Y. V.</creatorcontrib><creatorcontrib>Panchenkov, D. N.</creatorcontrib><title>Assessment of experimental OpenCV tracking algorithms for ultrasound videos</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms—CSRT and KCF—could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. 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A.</au><au>Klimov, D. D.</au><au>Nechunaev, A. A.</au><au>Prokhorenko, L. S.</au><au>Mishchenkov, D. S.</au><au>Nosova, A. G.</au><au>Astakhov, D. A.</au><au>Poduraev, Y. V.</au><au>Panchenkov, D. N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of experimental OpenCV tracking algorithms for ultrasound videos</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2023-04-25</date><risdate>2023</risdate><volume>13</volume><issue>1</issue><spage>6765</spage><epage>6765</epage><pages>6765-6765</pages><artnum>6765</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>This study aims to compare the tracking algorithms provided by the OpenCV library to use on ultrasound video. Despite the widespread application of this computer vision library, few works describe the attempts to use it to track the movement of liver tumors on ultrasound video. Movements of the neoplasms caused by the patient`s breath interfere with the positioning of the instruments during the process of biopsy and radio-frequency ablation. The main hypothesis of the experiment was that tracking neoplasms and correcting the position of the manipulator in case of using robotic-assisted surgery will allow positioning the instruments more precisely. Another goal of the experiment was to check if it is possible to ensure real-time tracking with at least 25 processed frames per second for standard definition video. OpenCV version 4.5.0 was used with 7 tracking algorithms from the extra modules package. They are: Boosting, CSRT, KCF, MedianFlow, MIL, MOSSE, TLD. More than 5600 frames of standard definition were processed during the experiment. Analysis of the results shows that two algorithms—CSRT and KCF—could solve the problem of tumor tracking. They lead the test with 70% and more of Intersection over Union and more than 85% successful searches. They could also be used in real-time processing with an average processing speed of up to frames per second in CSRT and 100 + frames per second for KCF. Tracking results reach the average deviation between centers of neoplasms to 2 mm and maximum deviation less than 5 mm. This experiment also shows that no frames made CSRT and KCF algorithms fail simultaneously. So, the hypothesis for future work is combining these algorithms to work together, with one of them—CSRT—as support for the KCF tracker on the rarely failed frames.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>37185281</pmid><doi>10.1038/s41598-023-30930-3</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 639/166/985 692/4028/546 Algorithms Biopsy Computer vision Computers Experiments Humanities and Social Sciences Humans Hypotheses Movement multidisciplinary Robotic surgery Robotic Surgical Procedures Science Science (multidisciplinary) Tumors Ultrasonic imaging Ultrasound |
title | Assessment of experimental OpenCV tracking algorithms for ultrasound videos |
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