You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
27 March 2014Seamless insertion of real pulmonary nodules in chest CT exams
The availability of large medical image datasets is critical in many applications such as training and testing of computer aided diagnosis (CAD) systems, evaluation of segmentation algorithms, and conducting perceptual studies. However, collection of large repositories of clinical images is hindered by the high cost and difficulties associated with both the accumulation of data and establishment of the ground truth. To address this problem, we are developing an image blending tool that allows users to modify or supplement existing datasets by seamlessly inserting a real lesion extracted from a source image into a different location on a target image. In this study we focus on the application of this tool to pulmonary nodules in chest CT exams. We minimize the impact of user skill on the perceived quality of the blended image by limiting user involvement to two simple steps: the user first draws a casual boundary around the nodule of interest in the source, and then selects the center of desired insertion area in the target. We demonstrate examples of the performance of the proposed system on samples taken from the Lung Image Database Consortium (LIDC) dataset, and compare the noise power spectrum (NPS) of blended nodules versus that of native nodules in simulated phantoms.
The alert did not successfully save. Please try again later.
Aria Pezeshk, Berkman Sahiner, Rongping Zeng, Adam Wunderlich, Weijie Chen, Nicholas Petrick, "Seamless insertion of real pulmonary nodules in chest CT exams," Proc. SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis, 90351K (27 March 2014); https://doi.org/10.1117/12.2043786