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We propose a method to establish the standard chest frame of reference (CFOR) using the rib cage in a lung CT scan. Such a reference frame is essential for referring to a certain location within a chest region and may facilitate the registration across multiple scans of a given subject as well as the comparative studies within a cohort of subjects. The robustness of the established CFOR was evaluated...
Estimation of nodule location and size is an important pre-processing step in some nodule segmentation algorithms to determine the size and location of the region of interest. Ideally, such estimation methods will consistently find the same nodule location irregardless of where the the seed point (provided either manually or by a nodule detection algorithm) is placed relative to the ldquotruerdquo...
Many nodule measurement methods rely on accurate segmentation of the nodule and may fail with complex nodule morphologies; often slight variations in segmentation result in large volume differences. A method, growth analysis from density (GAD), is presented that measures nodule growth without explicit segmentation through the application of a Gaussian weighting function to a region around the nodule,...
Assessing the precision in the estimation of lesion dimensions is a prerequisite for the determination of growth rates and response to therapy both in clinical practice and research. An initial study was designed and performed to evaluate three different marking methods: uni-dimensional (maximum diameter of nodule in-axial plane), manual volumetric and a computer assisted mark-up (CAM) method. The...
Automated nodule classification systems determine a model based on features extracted from documented databases of nodules. These databases cover a large size range and have an unequal distribution of malignant and benign nodules, leading to a high correlation between malignancy and size. For two recent studies in the literature, much of the reported performance of the system may be derived from size...
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