Inproceedings: an article in a conference proceedings.
3D Automated Lung Nodule Segmentation in HRCT
Title of the conference
MICCAI 2003, Medical Image Computing and Computer-Assisted Intervention, Proceedings of the 6th International Conference
Montréal, Canada, November 15-18, 2003
Randy E.E., Peters T.M.
Lecture Notes in Computer Science
A fully-automated 3D image analysis method is proposed to segment lung nodules in HRCT. A specific gray-level mathematical morphology operator, the SMDC-connection cost, acting in the 3D space of the thorax volume is defined in order to discriminate lung nodules from other dense (vascular) structures. Applied to clinical data concerning patients with pulmonary carcinoma, the proposed method detects isolated, juxtavascular and peripheral nodules with sizes ranging from 2 to 20 mm diameter. The segmentation accuracy was objectively evaluated on real and simulated nodules. The method showed a sensitivity and a specificity ranging from 85% to 97% and from 90% to 98%, respectively.
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