Saliency-guided automatic detection and segmentation of tumor in breast ultrasound images
• New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measur...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ramadan, Hiba [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood - Yan, Yinkun ELSEVIER, 2017, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:60 ; year:2020 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.bspc.2020.101945 |
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| 520 | |a • New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measure is proposed for result refinement. • Performance of the proposed method in terms of: tumor detection, tumor segmentation and speed. | ||
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10.1016/j.bspc.2020.101945 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001032.pica (DE-627)ELV050561227 (ELSEVIER)S1746-8094(20)30101-4 DE-627 ger DE-627 rakwb eng 610 VZ 630 640 610 VZ Ramadan, Hiba verfasserin aut Saliency-guided automatic detection and segmentation of tumor in breast ultrasound images 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measure is proposed for result refinement. • Performance of the proposed method in terms of: tumor detection, tumor segmentation and speed. Graph-based segmentation Elsevier Computer aided diagnosis Elsevier Tumor segmentation Elsevier Breast ultrasound Elsevier Tumor detection Elsevier Saliency score Elsevier Saliency detection Elsevier Active contours Elsevier Lachqar, Chaymae oth Tairi, Hamid oth Enthalten in Elsevier Yan, Yinkun ELSEVIER Independent influences of excessive body weight and elevated blood pressure from childhood on left ventricular geometric remodeling in adulthood 2017 Amsterdam [u.a.] (DE-627)ELV020088493 volume:60 year:2020 pages:0 https://doi.org/10.1016/j.bspc.2020.101945 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_60 AR 60 2020 0 |
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• New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measure is proposed for result refinement. • Performance of the proposed method in terms of: tumor detection, tumor segmentation and speed. |
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• New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measure is proposed for result refinement. • Performance of the proposed method in terms of: tumor detection, tumor segmentation and speed. |
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• New hybrid method for automatic detection and segmentation of tumor in breast ultrasound (BUS) images. • Saliency is used to emulate radiologist’s ability to detect the tumor region and background region in BUS image. • Graph-based approach is applied to segment lesion. • New saliency score measure is proposed for result refinement. • Performance of the proposed method in terms of: tumor detection, tumor segmentation and speed. |
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