Learning supervised descent directions for optic disc segmentation
Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD seg...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Annan [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
|---|---|
| Übergeordnetes Werk: |
volume:275 ; year:2018 ; day:31 ; month:01 ; pages:350-357 ; extent:8 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.neucom.2017.08.033 |
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| 520 | |a Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. | ||
| 520 | |a Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. | ||
| 700 | 1 | |a Niu, Zhiheng |4 oth | |
| 700 | 1 | |a Cheng, Jun |4 oth | |
| 700 | 1 | |a Yin, Fengshou |4 oth | |
| 700 | 1 | |a Wong, Damon Wing Kee |4 oth | |
| 700 | 1 | |a Yan, Shuicheng |4 oth | |
| 700 | 1 | |a Liu, Jiang |4 oth | |
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10.1016/j.neucom.2017.08.033 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001232.pica (DE-627)ELV041442253 (ELSEVIER)S0925-2312(17)31454-6 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Li, Annan verfasserin aut Learning supervised descent directions for optic disc segmentation 2018transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Niu, Zhiheng oth Cheng, Jun oth Yin, Fengshou oth Wong, Damon Wing Kee oth Yan, Shuicheng oth Liu, Jiang oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:275 year:2018 day:31 month:01 pages:350-357 extent:8 https://doi.org/10.1016/j.neucom.2017.08.033 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 275 2018 31 0131 350-357 8 |
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10.1016/j.neucom.2017.08.033 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001232.pica (DE-627)ELV041442253 (ELSEVIER)S0925-2312(17)31454-6 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Li, Annan verfasserin aut Learning supervised descent directions for optic disc segmentation 2018transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Niu, Zhiheng oth Cheng, Jun oth Yin, Fengshou oth Wong, Damon Wing Kee oth Yan, Shuicheng oth Liu, Jiang oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:275 year:2018 day:31 month:01 pages:350-357 extent:8 https://doi.org/10.1016/j.neucom.2017.08.033 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 275 2018 31 0131 350-357 8 |
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10.1016/j.neucom.2017.08.033 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001232.pica (DE-627)ELV041442253 (ELSEVIER)S0925-2312(17)31454-6 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Li, Annan verfasserin aut Learning supervised descent directions for optic disc segmentation 2018transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Niu, Zhiheng oth Cheng, Jun oth Yin, Fengshou oth Wong, Damon Wing Kee oth Yan, Shuicheng oth Liu, Jiang oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:275 year:2018 day:31 month:01 pages:350-357 extent:8 https://doi.org/10.1016/j.neucom.2017.08.033 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 275 2018 31 0131 350-357 8 |
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10.1016/j.neucom.2017.08.033 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001232.pica (DE-627)ELV041442253 (ELSEVIER)S0925-2312(17)31454-6 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Li, Annan verfasserin aut Learning supervised descent directions for optic disc segmentation 2018transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Niu, Zhiheng oth Cheng, Jun oth Yin, Fengshou oth Wong, Damon Wing Kee oth Yan, Shuicheng oth Liu, Jiang oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:275 year:2018 day:31 month:01 pages:350-357 extent:8 https://doi.org/10.1016/j.neucom.2017.08.033 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 275 2018 31 0131 350-357 8 |
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10.1016/j.neucom.2017.08.033 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001232.pica (DE-627)ELV041442253 (ELSEVIER)S0925-2312(17)31454-6 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Li, Annan verfasserin aut Learning supervised descent directions for optic disc segmentation 2018transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. Niu, Zhiheng oth Cheng, Jun oth Yin, Fengshou oth Wong, Damon Wing Kee oth Yan, Shuicheng oth Liu, Jiang oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:275 year:2018 day:31 month:01 pages:350-357 extent:8 https://doi.org/10.1016/j.neucom.2017.08.033 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 275 2018 31 0131 350-357 8 |
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Learning supervised descent directions for optic disc segmentation |
| author_sort |
Li, Annan |
| journal |
The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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eng |
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500 - Science |
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2018 |
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350 |
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Li, Annan |
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570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl |
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Elektronische Aufsätze |
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Li, Annan |
| doi_str_mv |
10.1016/j.neucom.2017.08.033 |
| dewey-full |
570 |
| title_sort |
learning supervised descent directions for optic disc segmentation |
| title_auth |
Learning supervised descent directions for optic disc segmentation |
| abstract |
Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. |
| abstractGer |
Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. |
| abstract_unstemmed |
Optic disc (OD) segmentation is an important step in analyzing the color fundus image. Most existing approaches are based on the shape prior and visual appearance of the OD boundary. However, the current ways of integrating the shape and appearance are simple. We argue that the performance of OD segmentation can be improved by better shape-appearance modeling. In this paper, we propose to learn a sequence of supervised descent directions between the coordinates of OD boundary and their surrounding visual appearances for OD segmentation. In addition, we introduce the histograms of gradient orientations to represent the OD appearance. Experimental results on six datasets clearly show that the proposed method improves the OD segmentation and outperforms the state-of-the-art. |
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GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA |
| title_short |
Learning supervised descent directions for optic disc segmentation |
| url |
https://doi.org/10.1016/j.neucom.2017.08.033 |
| remote_bool |
true |
| author2 |
Niu, Zhiheng Cheng, Jun Yin, Fengshou Wong, Damon Wing Kee Yan, Shuicheng Liu, Jiang |
| author2Str |
Niu, Zhiheng Cheng, Jun Yin, Fengshou Wong, Damon Wing Kee Yan, Shuicheng Liu, Jiang |
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10.1016/j.neucom.2017.08.033 |
| up_date |
2024-07-06T20:07:52.843Z |
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