Abstract: Radiographic detection of pulmonary nodules based on three-dimensional Hessian matrix is highly sensitive but
frequently produces false positive results in areas where blood vessels intersect. We propose a novel approach to pulmonary
nodule detection using Hessian matrix-based adaptive window structure analysis, in which the structure coefficients is used to
differentiate a voxel that belongs to a nodule or vascular structures, followed by construction of the 3D adaptive window to
analyze the local structure characteristics; the nodules were then detected using the discrimination function. The experimental
results on pulmonary CT images from 17 patients showed a 100% detection sensitivity for nodules of varying sizes and types,
with also significantly reduced false positive results generated by the vessel junctions. This approach provides valuable
assistance to follow-up positioning and segmentation of the pulmonary nodules.