Detection of juxta-pleural lung nodules in computed tomography images

A method for the detection of juxta-pleural lung nodules with radius <= 5 mm in chest computed tomography images is proposed. The lung volume is segmented using region-growing and refined with morphological operations and active contours to include juxta-pleural nodules. Nodule candidates are searched slice-wise inside the lung volume segmentation. Solid nodules are detected by selecting an appropriate threshold inside a representative sliding window. Sub-solid and non-solid nodules are enhanced with a multiscale Laplacian-of-Gaussian filtering prior to their detection. Obvious non-nodule candidates, namely small blood vessels, are discarded using fixed rules. Then, a support vector machine with radial basis function is trained with the remaining candidates to further reduce the number of false positives (FPs). The final system sensitivity is 57.4% with 4 FPs/scan. The performance is similar or better than state-of-the-art methods, especially when considering the high number and small radius of the studied juxta-pleural nodules.