Autonomous detection of solitary pulmonary nodules on CT images for computer-aided diagnosis

Wei, Ying; Jia, Tong; Lin, Min

doi:10.1109/ccdc.2011.5968933

Cited by 1 publication

(2 citation statements)

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“…[41] used Bounding box method, gray level thresholding and rolling ball algorithm for segmenting lung nodules followed by a dot enhancement filter applied on three directions. Thresholding and multi scale morphological filtering were implemented by [42] to detect SPNs. [19] applied thresholding techniques followed by watershed algorithm and region growing technique to attain more accurate segmentation of nodules.…”

Section: Thresholdingmentioning

confidence: 99%

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Techniques for Detection of Solitary Pulmonary Nodules in Human Lung and Their Classifications -A Survey

Bhavanishankar¹,

M.V²

2015

IJCI

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Lung cancer is proving to be a catastrophic threat to the mankind and is main cause of deaths among other cancer related casualties. The presence of solitary pulmonary nodules in human lungs in the form of benign or malignant determines the gravity of lung ailment. This survey focusses on different techniques used to detect and classify the lung nodules which in turn will assist the domain experts for better diagnosis. Among many imaging modalities Computed Tomography (CT) being the most sought after because of its high resolution, isotropic acquisition which helps in locating the lung lesions. Since the volume of the CT scans are very large, Computer Aided Detection/Diagnosis (CAD/x) has more advantages in addition to manual interpretation with respect to speed and accuracy. This paper attempts to summarize various methods that have been proposed by several authors over the years of their research.

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Section: Thresholdingmentioning

confidence: 99%

“…Classification in frequency domain using SVM classifier was performed by [43] [66]. [42] used SVM and weighted modifies Mahalanobis distance measure to nodule classification. Shape and histogram based analysis were used by [67].…”

Section: Svm Based Classificationmentioning

confidence: 99%

Techniques for Detection of Solitary Pulmonary Nodules in Human Lung and Their Classifications -A Survey

Bhavanishankar¹,

M.V²

2015

IJCI

View full text Add to dashboard Cite

show abstract

Autonomous detection of solitary pulmonary nodules on CT images for computer-aided diagnosis

Cited by 1 publication

References 10 publications

Techniques for Detection of Solitary Pulmonary Nodules in Human Lung and Their Classifications -A Survey

Techniques for Detection of Solitary Pulmonary Nodules in Human Lung and Their Classifications -A Survey

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