Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping
<p>Surgical procedures such as laparoscopic and robotic surgeries are popular since they are invasive in nature and use miniaturized surgical instruments for small incisions. Tracking of the instruments (graspers, needle drivers) and field of view from the stereoscopic camera during surgery co...
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| مؤلفون آخرون: | , , , , , , , , |
| منشور في: |
2019
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| _version_ | 1864513567458328576 |
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| author | Sarada Prasad Dakua (14151789) |
| author2 | Julien Abinahed (14151792) Ayman Zakaria (714824) Shidin Balakrishnan (14150580) Georges Younes (14151795) Nikhil Navkar (14151798) Abdulla Al-Ansari (14150583) Xiaojun Zhai (9040469) Faycal Bensaali (12427401) Abbes Amira (6952001) |
| author2_role | author author author author author author author author author |
| author_facet | Sarada Prasad Dakua (14151789) Julien Abinahed (14151792) Ayman Zakaria (714824) Shidin Balakrishnan (14150580) Georges Younes (14151795) Nikhil Navkar (14151798) Abdulla Al-Ansari (14150583) Xiaojun Zhai (9040469) Faycal Bensaali (12427401) Abbes Amira (6952001) |
| author_role | author |
| dc.creator.none.fl_str_mv | Sarada Prasad Dakua (14151789) Julien Abinahed (14151792) Ayman Zakaria (714824) Shidin Balakrishnan (14150580) Georges Younes (14151795) Nikhil Navkar (14151798) Abdulla Al-Ansari (14150583) Xiaojun Zhai (9040469) Faycal Bensaali (12427401) Abbes Amira (6952001) |
| dc.date.none.fl_str_mv | 2019-07-15T21:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1007/s11548-019-02030-z |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Moving_object_tracking_in_clinical_scenarios_application_to_cardiac_surgery_and_cerebral_aneurysm_clipping/21597585 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Health sciences Health services and systems Cerebral aneurysm Segmentation Object tracking Heart surgery Brain aneurysm clipping Level sets |
| dc.title.none.fl_str_mv | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>Surgical procedures such as laparoscopic and robotic surgeries are popular since they are invasive in nature and use miniaturized surgical instruments for small incisions. Tracking of the instruments (graspers, needle drivers) and field of view from the stereoscopic camera during surgery could further help the surgeons to remain focussed and reduce the probability of committing any mistakes. Tracking is usually preferred in computerized video surveillance, traffic monitoring, military surveillance system, and vehicle navigation. Despite the numerous efforts over the last few years, object tracking still remains an open research problem, mainly due to motion blur, image noise, lack of image texture, and occlusion. Most of the existing object tracking methods are time-consuming and less accurate when the input video contains high volume of information and more number of instruments. This paper presents a variational framework to track the motion of moving objects in surgery videos. The key contributions are as follows: (1) A denoising method using stochastic resonance in maximal overlap discrete wavelet transform is proposed and (2) a robust energy functional based on Bhattacharyya coefficient to match the target region in the first frame of the input sequence with the subsequent frames using a similarity metric is developed. A modified affine transformation-based registration is used to estimate the motion of the features following an active contour-based segmentation method to converge the contour resulted from the registration process. The proposed method has been implemented on publicly available databases; the results are found satisfactory. Overlap index (OI) is used to evaluate the tracking performance, and the maximum OI is found to be 76% and 88% on private data and public data sequences.</p><h2>Other Information</h2> <p> Published in: International Journal of Computer Assisted Radiology and Surgery<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s11548-019-02030-z" target="_blank">http://dx.doi.org/10.1007/s11548-019-02030-z</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_fb2d9182c924cacc51cf9c1568b5b8b5 |
| identifier_str_mv | 10.1007/s11548-019-02030-z |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/21597585 |
| publishDate | 2019 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clippingSarada Prasad Dakua (14151789)Julien Abinahed (14151792)Ayman Zakaria (714824)Shidin Balakrishnan (14150580)Georges Younes (14151795)Nikhil Navkar (14151798)Abdulla Al-Ansari (14150583)Xiaojun Zhai (9040469)Faycal Bensaali (12427401)Abbes Amira (6952001)Biomedical and clinical sciencesClinical sciencesHealth sciencesHealth services and systemsCerebral aneurysmSegmentationObject trackingHeart surgeryBrain aneurysm clippingLevel sets<p>Surgical procedures such as laparoscopic and robotic surgeries are popular since they are invasive in nature and use miniaturized surgical instruments for small incisions. Tracking of the instruments (graspers, needle drivers) and field of view from the stereoscopic camera during surgery could further help the surgeons to remain focussed and reduce the probability of committing any mistakes. Tracking is usually preferred in computerized video surveillance, traffic monitoring, military surveillance system, and vehicle navigation. Despite the numerous efforts over the last few years, object tracking still remains an open research problem, mainly due to motion blur, image noise, lack of image texture, and occlusion. Most of the existing object tracking methods are time-consuming and less accurate when the input video contains high volume of information and more number of instruments. This paper presents a variational framework to track the motion of moving objects in surgery videos. The key contributions are as follows: (1) A denoising method using stochastic resonance in maximal overlap discrete wavelet transform is proposed and (2) a robust energy functional based on Bhattacharyya coefficient to match the target region in the first frame of the input sequence with the subsequent frames using a similarity metric is developed. A modified affine transformation-based registration is used to estimate the motion of the features following an active contour-based segmentation method to converge the contour resulted from the registration process. The proposed method has been implemented on publicly available databases; the results are found satisfactory. Overlap index (OI) is used to evaluate the tracking performance, and the maximum OI is found to be 76% and 88% on private data and public data sequences.</p><h2>Other Information</h2> <p> Published in: International Journal of Computer Assisted Radiology and Surgery<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s11548-019-02030-z" target="_blank">http://dx.doi.org/10.1007/s11548-019-02030-z</a></p>2019-07-15T21:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s11548-019-02030-zhttps://figshare.com/articles/journal_contribution/Moving_object_tracking_in_clinical_scenarios_application_to_cardiac_surgery_and_cerebral_aneurysm_clipping/21597585CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/215975852019-07-15T21:00:00Z |
| spellingShingle | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping Sarada Prasad Dakua (14151789) Biomedical and clinical sciences Clinical sciences Health sciences Health services and systems Cerebral aneurysm Segmentation Object tracking Heart surgery Brain aneurysm clipping Level sets |
| status_str | publishedVersion |
| title | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| title_full | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| title_fullStr | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| title_full_unstemmed | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| title_short | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| title_sort | Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clipping |
| topic | Biomedical and clinical sciences Clinical sciences Health sciences Health services and systems Cerebral aneurysm Segmentation Object tracking Heart surgery Brain aneurysm clipping Level sets |