A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks
A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tort...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Almasi, Sepideh [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Rechteinformationen: |
Nutzungsrecht: Copyright © 2014 Elsevier B.V. All rights reserved. |
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| Schlagwörter: |
Imaging, Three-Dimensional - methods |
|---|
| Übergeordnetes Werk: |
Enthalten in: Medical image analysis - Amsterdam [u.a.] : Elsevier, 1996, 20(2015), 1, Seite 208-223 |
|---|---|
| Übergeordnetes Werk: |
volume:20 ; year:2015 ; number:1 ; pages:208-223 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.media.2014.11.007 |
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OLC1960852817 |
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| 520 | |a A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. | ||
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10.1016/j.media.2014.11.007 doi PQ20160617 (DE-627)OLC1960852817 (DE-599)GBVOLC1960852817 (PRQ)c1516-6945b9c62cb8d7e685a8a7dd0783a06781710209019c9086f8dbbecb62a6ab7f0 (KEY)0392983320150000020000100208novelmethodforidentifyingagraphbasedrepresentation DE-627 ger DE-627 rakwb eng 004 ZDB Almasi, Sepideh verfasserin aut A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. Nutzungsrecht: Copyright © 2014 Elsevier B.V. All rights reserved. Imaging, Three-Dimensional - methods Microscopy, Fluorescence - methods Microvessels - anatomy & histology Xu, Xiaoyin oth Ben-Zvi, Ayal oth Lacoste, Baptiste oth Gu, Chenghua oth Miller, Eric L oth Enthalten in Medical image analysis Amsterdam [u.a.] : Elsevier, 1996 20(2015), 1, Seite 208-223 (DE-627)223260010 (DE-600)1356436-5 (DE-576)080160034 1361-8415 nnns volume:20 year:2015 number:1 pages:208-223 http://dx.doi.org/10.1016/j.media.2014.11.007 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25515433 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_4219 AR 20 2015 1 208-223 |
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10.1016/j.media.2014.11.007 doi PQ20160617 (DE-627)OLC1960852817 (DE-599)GBVOLC1960852817 (PRQ)c1516-6945b9c62cb8d7e685a8a7dd0783a06781710209019c9086f8dbbecb62a6ab7f0 (KEY)0392983320150000020000100208novelmethodforidentifyingagraphbasedrepresentation DE-627 ger DE-627 rakwb eng 004 ZDB Almasi, Sepideh verfasserin aut A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. Nutzungsrecht: Copyright © 2014 Elsevier B.V. All rights reserved. Imaging, Three-Dimensional - methods Microscopy, Fluorescence - methods Microvessels - anatomy & histology Xu, Xiaoyin oth Ben-Zvi, Ayal oth Lacoste, Baptiste oth Gu, Chenghua oth Miller, Eric L oth Enthalten in Medical image analysis Amsterdam [u.a.] : Elsevier, 1996 20(2015), 1, Seite 208-223 (DE-627)223260010 (DE-600)1356436-5 (DE-576)080160034 1361-8415 nnns volume:20 year:2015 number:1 pages:208-223 http://dx.doi.org/10.1016/j.media.2014.11.007 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25515433 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_4219 AR 20 2015 1 208-223 |
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A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks |
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A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks |
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Almasi, Sepideh |
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novel method for identifying a graph-based representation of 3-d microvascular networks from fluorescence microscopy image stacks |
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A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks |
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A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. |
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A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. |
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A novel approach to determine the global topological structure of a microvasculature network from noisy and low-resolution fluorescence microscopy data that does not require the detailed segmentation of the vessel structure is proposed here. The method is most appropriate for problems where the tortuosity of the network is relatively low and proceeds by directly computing a piecewise linear approximation to the vasculature skeleton through the construction of a graph in three dimensions whose edges represent the skeletal approximation and vertices are located at Critical Points (CPs) on the microvasculature. The CPs are defined as vessel junctions or locations of relatively large curvature along the centerline of a vessel. Our method consists of two phases. First, we provide a CP detection technique that, for junctions in particular, does not require any a priori geometric information such as direction or degree. Second, connectivity between detected nodes is determined via the solution of a Binary Integer Program (BIP) whose variables determine whether a potential edge between nodes is or is not included in the final graph. The utility function in this problem reflects both intensity-based and structural information along the path connecting the two nodes. Qualitative and quantitative results confirm the usefulness and accuracy of this method. This approach provides a mean of correctly capturing the connectivity patterns in vessels that are missed by more traditional segmentation and binarization schemes because of imperfections in the images which manifest as dim or broken vessels. |
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A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks |
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