@inproceedings{933441b206f2446e83fb02e3831e3af9,
title = "Application of CT acquisition parameters as features in computer-aided detection for CT colonography",
abstract = "Studies have indicated that the acquisition parameters of computed tomography (CT) scans can have significant effect on the accuracy of computer-aided detection (CAD) in CT colonography. We investigated whether these parameters can be used as external features with conventional image-based features to improve CAD performance. A CAD scheme was trained with the CT colonography data of 886 patients, and it was tested with an independent set of 705 CT colonography cases. The results indicate that some CT acquisition parameters can be used successfully as features of the detected lesion candidates for improving the detection accuracy of CAD for flat lesions and carcinomas.",
keywords = "Computed tomographic colonography, computer-aided detection, CT acquisition, polyp detection, virtual colonoscopy",
author = "N{\"a}ppi, {Janne J.} and Don Rockey and Daniele Regge and Hiroyuki Yoshida",
year = "2012",
doi = "10.1007/978-3-642-33612-6_8",
language = "English",
isbn = "9783642336119",
volume = "7601 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "69--77",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
note = "4th International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 ; Conference date: 01-10-2012 Through 01-10-2012",
}