<![CDATA[The growth rate of the Pulmonary nodule increases the doubling time of the Pulmonary nodule, which is a significant indicator of malignancy. The mean diameter measurement of the Pulmonary nodule contributes to the assessment of lung cancer based on the doubling time. Small nodule size, partial volume effect, irregular shape, juxtapleural, and juxtavascular nodules are difficult to measure. This work addresses these measurement challenges using an image processing pipeline consisting of image segmentation and quantification. The computed tomography (CT) image preprocessing, segmentation, edge detection, and nodule measurement framework is proposed to extract the nodules from the CT image and then quantify them by measuring their mean diameter. A novel pulmonary nodules magnitude ratio (PNMR) is proposed to establish the sattastical relationship between the nodule and corresponding parenchyma size. The LNMR is evaluated against the synthetic nodules that express the nodule growth rate. This work contributes automatic nodule detection, semiautomatic nodule measurement, and PNMR evaluation for more reliable detection and quantification of Pulmonary nodules.]]>
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