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Proceedings Paper

Pulmonary nodule detection in PET/CT images: improved approach using combined nodule detection and hybrid FP reduction
Author(s): Atsushi Teramoto; Hiroshi Fujita; Yoya Tomita; Katsuaki Takahashi; Osamu Yamamuro; Tsuneo Tamaki
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Paper Abstract

In this study, an automated scheme for detecting pulmonary nodules in PET/CT images has been proposed using combined detection and hybrid false-positive (FP) reduction techniques. The initial nodule candidates were detected separately from CT and PET images. FPs were then eliminated in the initial candidates by using support vector machine with characteristic values obtained from CT and PET images. In the experiment, we evaluated proposed method using 105 cases of PET/CT images that were obtained in the cancer-screening program. We evaluated true positive fraction (TPF) and FP / case. As a result, TPFs of CT and PET detections were 0.76 and 0.44, respectively. However, by integrating the both results, TPF was reached to 0.82 with 5.14 FPs/case. These results indicate that our method may be of practical use for the detection of pulmonary nodules using PET/CT images.

Paper Details

Date Published: 23 February 2012
PDF: 6 pages
Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83152V (23 February 2012); doi: 10.1117/12.912102
Show Author Affiliations
Atsushi Teramoto, Fujita Health Univ. (Japan)
Hiroshi Fujita, Gifu Univ. School of Medicine (Japan)
Yoya Tomita, East Nagoya Imaging Diagnosis Ctr. (Japan)
Katsuaki Takahashi, East Nagoya Imaging Diagnosis Ctr. (Japan)
Osamu Yamamuro, East Nagoya Imaging Diagnosis Ctr. (Japan)
Tsuneo Tamaki, East Nagoya Imaging Diagnosis Ctr. (Japan)

Published in SPIE Proceedings Vol. 8315:
Medical Imaging 2012: Computer-Aided Diagnosis
Bram van Ginneken; Carol L. Novak, Editor(s)

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