Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction

Atsushi Teramoto; Hiroshi Fujita; Yoya Tomita; Katsuaki Takahashi; Osamu Yamamuro; Tsuneo Tamaki

doi:10.1117/12.912102

Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction

Atsushi Teramoto
, Hiroshi Fujita
, Yoya Tomita
, Katsuaki Takahashi
, Osamu Yamamuro
, Tsuneo Tamaki

Faculty of Radiological Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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.

Original language	English
Title of host publication	Medical Imaging 2012
Subtitle of host publication	Computer-Aided Diagnosis
DOIs	https://doi.org/10.1117/12.912102
Publication status	Published - 2012
Event	Medical Imaging 2012: Computer-Aided Diagnosis - San Diego, CA, United States Duration: 07-02-2012 → 09-02-2012

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	8315
ISSN (Print)	1605-7422

Other

Other	Medical Imaging 2012: Computer-Aided Diagnosis
Country/Territory	United States
City	San Diego, CA
Period	07-02-12 → 09-02-12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Biomaterials
Atomic and Molecular Physics, and Optics
Radiology Nuclear Medicine and imaging

Access to Document

10.1117/12.912102

Cite this

Teramoto, A., Fujita, H., Tomita, Y., Takahashi, K., Yamamuro, O., & Tamaki, T. (2012). Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction. In Medical Imaging 2012: Computer-Aided Diagnosis Article 83152V (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8315). https://doi.org/10.1117/12.912102

@inproceedings{a1f82fdccbea433c84c9372427db39da,

title = "Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction",

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.",

author = "Atsushi Teramoto and Hiroshi Fujita and Yoya Tomita and Katsuaki Takahashi and Osamu Yamamuro and Tsuneo Tamaki",

year = "2012",

doi = "10.1117/12.912102",

language = "English",

isbn = "9780819489647",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

booktitle = "Medical Imaging 2012",

note = "Medical Imaging 2012: Computer-Aided Diagnosis ; Conference date: 07-02-2012 Through 09-02-2012",

}

Teramoto, A, Fujita, H, Tomita, Y, Takahashi, K, Yamamuro, O & Tamaki, T 2012, Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction. in Medical Imaging 2012: Computer-Aided Diagnosis., 83152V, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 8315, Medical Imaging 2012: Computer-Aided Diagnosis, San Diego, CA, United States, 07-02-12. https://doi.org/10.1117/12.912102

Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction. / Teramoto, Atsushi; Fujita, Hiroshi; Tomita, Yoya et al.
Medical Imaging 2012: Computer-Aided Diagnosis. 2012. 83152V (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8315).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Pulmonary nodule detection in PET/CT images

T2 - Medical Imaging 2012: Computer-Aided Diagnosis

AU - Teramoto, Atsushi

AU - Fujita, Hiroshi

AU - Tomita, Yoya

AU - Takahashi, Katsuaki

AU - Yamamuro, Osamu

AU - Tamaki, Tsuneo

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

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UR - https://www.scopus.com/pages/publications/84874886051#tab=citedBy

U2 - 10.1117/12.912102

DO - 10.1117/12.912102

M3 - Conference contribution

AN - SCOPUS:84874886051

SN - 9780819489647

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2012

Y2 - 7 February 2012 through 9 February 2012

ER -

Pulmonary nodule detection in PET/CT images: Improved approach using combined nodule detection and hybrid FP reduction

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