A modified gradient correlation filter for image segmentation: Application to airway and bowel.
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| Title: | A modified gradient correlation filter for image segmentation: Application to airway and bowel. |
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| Authors: | Sensakovic, William F.1 wfsensak@uchicago.edu, Starkey, Adam1, Armato, Samuel G.1 |
| Source: | Medical Physics. Feb2009, Vol. 36 Issue 2, p480-485. 6p. 4 Black and White Photographs, 1 Diagram, 3 Graphs. |
| Subjects: | Medical imaging systems, Diagnostic imaging, Tomography, Airway (Anatomy), Lungs, Cardiopulmonary system, Medical radiography |
| Abstract: | The segmentation of structures of interest from medical images may incorrectly include adjacent structures in the segmented image (i.e., false positives). This study introduces a family of gradient correlation filters that reduce false positives in the segmented image by comparing the segmented region gradients with a user-defined model. A gradient correlation filter was applied to a database of clinical computed tomography scans for the task of differentiating airway from lung regions and bowel from lung regions. The results were evaluated using receiver-operating characteristic analysis and demonstrated excellent results for both the airway/lung and bowel/lung classification tasks. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Physics is the property of Wiley-Blackwell 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 | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 36356415 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A modified gradient correlation filter for image segmentation: Application to airway and bowel. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sensakovic%2C+William+F%2E%22">Sensakovic, William F.</searchLink><relatesTo>1</relatesTo><i> wfsensak@uchicago.edu</i><br /><searchLink fieldCode="AR" term="%22Starkey%2C+Adam%22">Starkey, Adam</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Armato%2C+Samuel+G%2E%22">Armato, Samuel G.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Physics%22">Medical Physics</searchLink>. Feb2009, Vol. 36 Issue 2, p480-485. 6p. 4 Black and White Photographs, 1 Diagram, 3 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Medical+imaging+systems%22">Medical imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnostic+imaging%22">Diagnostic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Tomography%22">Tomography</searchLink><br /><searchLink fieldCode="DE" term="%22Airway+%28Anatomy%29%22">Airway (Anatomy)</searchLink><br /><searchLink fieldCode="DE" term="%22Lungs%22">Lungs</searchLink><br /><searchLink fieldCode="DE" term="%22Cardiopulmonary+system%22">Cardiopulmonary system</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+radiography%22">Medical radiography</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The segmentation of structures of interest from medical images may incorrectly include adjacent structures in the segmented image (i.e., false positives). This study introduces a family of gradient correlation filters that reduce false positives in the segmented image by comparing the segmented region gradients with a user-defined model. A gradient correlation filter was applied to a database of clinical computed tomography scans for the task of differentiating airway from lung regions and bowel from lung regions. The results were evaluated using receiver-operating characteristic analysis and demonstrated excellent results for both the airway/lung and bowel/lung classification tasks. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Physics is the property of Wiley-Blackwell 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: 10.1118/1.3056461 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 6 StartPage: 480 Subjects: – SubjectFull: Medical imaging systems Type: general – SubjectFull: Diagnostic imaging Type: general – SubjectFull: Tomography Type: general – SubjectFull: Airway (Anatomy) Type: general – SubjectFull: Lungs Type: general – SubjectFull: Cardiopulmonary system Type: general – SubjectFull: Medical radiography Type: general Titles: – TitleFull: A modified gradient correlation filter for image segmentation: Application to airway and bowel. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sensakovic, William F. – PersonEntity: Name: NameFull: Starkey, Adam – PersonEntity: Name: NameFull: Armato, Samuel G. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2009 Type: published Y: 2009 Identifiers: – Type: issn-print Value: 00942405 Numbering: – Type: volume Value: 36 – Type: issue Value: 2 Titles: – TitleFull: Medical Physics Type: main |
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