Application of the 3D slicer chest imaging platform segmentation algorithm for large lung nodule delineation.

ABSTRACT:

Purpose

Accurate segmentation of lung nodules is crucial in the development of imaging biomarkers for predicting malignancy of the nodules. Manual segmentation is time consuming and affected by inter-observer variability. We evaluated the robustness and accuracy of a publically available semiautomatic segmentation algorithm that is implemented in the 3D Slicer Chest Imaging Platform (CIP) and compared it with the performance of manual segmentation.

Methods

CT images of 354 manually segmented nodules were downloaded from the LIDC database. Four radiologists performed the manual segmentation and assessed various nodule characteristics. The semiautomatic CIP segmentation was initialized using the centroid of the manual segmentations, thereby generating four contours for each no

SUBMITTER: Yip SSF 

PROVIDER: S-EPMC5464594 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature