Real-Time Task Recognition in Cataract Surgery Videos Using Adaptive Spatiotemporal Polynomials.
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| Title: | Real-Time Task Recognition in Cataract Surgery Videos Using Adaptive Spatiotemporal Polynomials. |
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| Authors: | Quellec, Gwenole1, Lamard, Mathieu2, Cochener, Beatrice2, Cazuguel, Guy3 |
| Source: | IEEE Transactions on Medical Imaging. Apr2015, Vol. 34 Issue 4, p877-887. 11p. |
| Subjects: | Cataract surgery, Ophthalmic surgery, Eye physiology, Fuzzy systems, Algorithms, Spatiotemporal processes |
| Abstract: | This paper introduces a new algorithm for recognizing surgical tasks in real-time in a video stream. The goal is to communicate information to the surgeon in due time during a video-monitored surgery. The proposed algorithm is applied to cataract surgery, which is the most common eye surgery. To compensate for eye motion and zoom level variations, cataract surgery videos are first normalized. Then, the motion content of short video subsequences is characterized with spatiotemporal polynomials: a multiscale motion characterization based on adaptive spatiotemporal polynomials is presented. The proposed solution is particularly suited to characterize deformable moving objects with fuzzy borders, which are typically found in surgical videos. Given a target surgical task, the system is trained to identify which spatiotemporal polynomials are usually extracted from videos when and only when this task is being performed. These key spatiotemporal polynomials are then searched in new videos to recognize the target surgical task. For improved performances, the system jointly adapts the spatiotemporal polynomial basis and identifies the key spatiotemporal polynomials using the multiple-instance learning paradigm. The proposed system runs in real-time and outperforms the previous solution from our group, both for surgical task recognition (A_z = 0.851 on average, as opposed to A_z = 0.794 previously) and for the joint segmentation and recognition of surgical tasks (A_z = 0.856 on average, as opposed to A_z = 0.832 previously). [ABSTRACT FROM PUBLISHER] |
| Copyright of IEEE Transactions on Medical Imaging is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 101862874 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Real-Time Task Recognition in Cataract Surgery Videos Using Adaptive Spatiotemporal Polynomials. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Quellec%2C+Gwenole%22">Quellec, Gwenole</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Lamard%2C+Mathieu%22">Lamard, Mathieu</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Cochener%2C+Beatrice%22">Cochener, Beatrice</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Cazuguel%2C+Guy%22">Cazuguel, Guy</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Medical+Imaging%22">IEEE Transactions on Medical Imaging</searchLink>. Apr2015, Vol. 34 Issue 4, p877-887. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Cataract+surgery%22">Cataract surgery</searchLink><br /><searchLink fieldCode="DE" term="%22Ophthalmic+surgery%22">Ophthalmic surgery</searchLink><br /><searchLink fieldCode="DE" term="%22Eye+physiology%22">Eye physiology</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+systems%22">Fuzzy systems</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Spatiotemporal+processes%22">Spatiotemporal processes</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This paper introduces a new algorithm for recognizing surgical tasks in real-time in a video stream. The goal is to communicate information to the surgeon in due time during a video-monitored surgery. The proposed algorithm is applied to cataract surgery, which is the most common eye surgery. To compensate for eye motion and zoom level variations, cataract surgery videos are first normalized. Then, the motion content of short video subsequences is characterized with spatiotemporal polynomials: a multiscale motion characterization based on adaptive spatiotemporal polynomials is presented. The proposed solution is particularly suited to characterize deformable moving objects with fuzzy borders, which are typically found in surgical videos. Given a target surgical task, the system is trained to identify which spatiotemporal polynomials are usually extracted from videos when and only when this task is being performed. These key spatiotemporal polynomials are then searched in new videos to recognize the target surgical task. For improved performances, the system jointly adapts the spatiotemporal polynomial basis and identifies the key spatiotemporal polynomials using the multiple-instance learning paradigm. The proposed system runs in real-time and outperforms the previous solution from our group, both for surgical task recognition (A_z = 0.851 on average, as opposed to A_z = 0.794 previously) and for the joint segmentation and recognition of surgical tasks (A_z = 0.856 on average, as opposed to A_z = 0.832 previously). [ABSTRACT FROM PUBLISHER] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Medical Imaging is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TMI.2014.2366726 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 877 Subjects: – SubjectFull: Cataract surgery Type: general – SubjectFull: Ophthalmic surgery Type: general – SubjectFull: Eye physiology Type: general – SubjectFull: Fuzzy systems Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Spatiotemporal processes Type: general Titles: – TitleFull: Real-Time Task Recognition in Cataract Surgery Videos Using Adaptive Spatiotemporal Polynomials. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Quellec, Gwenole – PersonEntity: Name: NameFull: Lamard, Mathieu – PersonEntity: Name: NameFull: Cochener, Beatrice – PersonEntity: Name: NameFull: Cazuguel, Guy IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 02780062 Numbering: – Type: volume Value: 34 – Type: issue Value: 4 Titles: – TitleFull: IEEE Transactions on Medical Imaging Type: main |
| ResultId | 1 |
