Li et al., 2016 - Google Patents
Segmentation of pulmonary nodules using adaptive local region energy with probability density function-based similarity distance and multi-features clusteringLi et al., 2016
View HTML- Document ID
- 8395427557252784951
- Author
- Li B
- Chen Q
- Peng G
- Guo Y
- Chen K
- Tian L
- Ou S
- Wang L
- Publication year
- Publication venue
- BioMedical Engineering OnLine
External Links
Snippet
Background Pulmonary nodules in computerized tomography (CT) images are potential manifestations of lung cancer. Segmentation of potential nodule objects is the first necessary and crucial step in computer-aided detection system of pulmonary nodules. The …
- 230000011218 segmentation 0 title abstract description 196
Classifications
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- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G06T2207/30048—Heart; Cardiac
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- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/30004—Biomedical image processing
- G06T2207/30061—Lung
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- G—PHYSICS
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- G06T2207/10081—Computed x-ray tomography [CT]
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- G06T2207/20116—Active contour; Active surface; Snakes
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- G06T2207/20156—Automatic seed setting
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