Computer-Aided Diagnosis System for Comparative Reading of Helical CT Images for the Detection of Lung Cancer

Hitoshi SATOH; Yuji UKAI; Noboru NIKI; Kenji EGUCHI; Kiyoshi MORI; Hironobu OHMATSU; Ryutarou KAKINUMA; Masahiro KANEKO; Noriyuki MORIYAMA

Computer-Aided Diagnosis System for Comparative Reading of Helical CT Images for the Detection of Lung Cancer

Hitoshi SATOH, Yuji UKAI, Noboru NIKI, Kenji EGUCHI, Kiyoshi MORI, Hironobu OHMATSU, Ryutarou KAKINUMA, Masahiro KANEKO, Noriyuki MORIYAMA

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In this paper, we present a computer-aided diagnosis (CAD) system to automatically detect lung cancer candidates at an early stage using a present and a past helical CT screening. We have developed a slice matching algorithm that can automatically match the slice images of a past CT scan to those of a present CT scan in order to detect changes in the lung fields over time. The slice matching algorithm consists of two main process: the process of extraction of the lungs, heart, and descending aorta and the process of matching slices of the present and past CT images using the information of the lungs, heart, and descending aorta. To evaluate the performance of this algorithm, we applied it to 50 subjects (total of 150 scans) screened between 1993 and 1998. From these scans, we selected 100 pairs for evaluation (each pair consisted of scans for the same subject). The algorithm correctly matched 88 out of the 100 pairs. The slice images for the present and past CT scans are displayed in parallel on the CRT monitor. Feature measurements of the suspicious regions are shown on the relevant images to facilitate identification of changes in size, shape, and intensity. The experimental results indicate that the CAD system can be effectively used in clinical practice to increase the speed and accuracy of routine diagnosis.

Publication: IEICE TRANSACTIONS on Information Vol.E84-D No.1 pp.161-170

Publication Date: 2001/01/01

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Type of Manuscript: PAPER

Category: Image Processing, Image Pattern Recognition

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Hitoshi SATOH, Yuji UKAI, Noboru NIKI, Kenji EGUCHI, Kiyoshi MORI, Hironobu OHMATSU, Ryutarou KAKINUMA, Masahiro KANEKO, Noriyuki MORIYAMA, "Computer-Aided Diagnosis System for Comparative Reading of Helical CT Images for the Detection of Lung Cancer" in IEICE TRANSACTIONS on Information, vol. E84-D, no. 1, pp. 161-170, January 2001, doi: .
Abstract: In this paper, we present a computer-aided diagnosis (CAD) system to automatically detect lung cancer candidates at an early stage using a present and a past helical CT screening. We have developed a slice matching algorithm that can automatically match the slice images of a past CT scan to those of a present CT scan in order to detect changes in the lung fields over time. The slice matching algorithm consists of two main process: the process of extraction of the lungs, heart, and descending aorta and the process of matching slices of the present and past CT images using the information of the lungs, heart, and descending aorta. To evaluate the performance of this algorithm, we applied it to 50 subjects (total of 150 scans) screened between 1993 and 1998. From these scans, we selected 100 pairs for evaluation (each pair consisted of scans for the same subject). The algorithm correctly matched 88 out of the 100 pairs. The slice images for the present and past CT scans are displayed in parallel on the CRT monitor. Feature measurements of the suspicious regions are shown on the relevant images to facilitate identification of changes in size, shape, and intensity. The experimental results indicate that the CAD system can be effectively used in clinical practice to increase the speed and accuracy of routine diagnosis.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_1_161/_p

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@ARTICLE{e84-d_1_161,
author={Hitoshi SATOH, Yuji UKAI, Noboru NIKI, Kenji EGUCHI, Kiyoshi MORI, Hironobu OHMATSU, Ryutarou KAKINUMA, Masahiro KANEKO, Noriyuki MORIYAMA, },
journal={IEICE TRANSACTIONS on Information},
title={Computer-Aided Diagnosis System for Comparative Reading of Helical CT Images for the Detection of Lung Cancer},
year={2001},
volume={E84-D},
number={1},
pages={161-170},
abstract={In this paper, we present a computer-aided diagnosis (CAD) system to automatically detect lung cancer candidates at an early stage using a present and a past helical CT screening. We have developed a slice matching algorithm that can automatically match the slice images of a past CT scan to those of a present CT scan in order to detect changes in the lung fields over time. The slice matching algorithm consists of two main process: the process of extraction of the lungs, heart, and descending aorta and the process of matching slices of the present and past CT images using the information of the lungs, heart, and descending aorta. To evaluate the performance of this algorithm, we applied it to 50 subjects (total of 150 scans) screened between 1993 and 1998. From these scans, we selected 100 pairs for evaluation (each pair consisted of scans for the same subject). The algorithm correctly matched 88 out of the 100 pairs. The slice images for the present and past CT scans are displayed in parallel on the CRT monitor. Feature measurements of the suspicious regions are shown on the relevant images to facilitate identification of changes in size, shape, and intensity. The experimental results indicate that the CAD system can be effectively used in clinical practice to increase the speed and accuracy of routine diagnosis.},
keywords={},
doi={},
ISSN={},
month={January},}

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TY - JOUR
TI - Computer-Aided Diagnosis System for Comparative Reading of Helical CT Images for the Detection of Lung Cancer
T2 - IEICE TRANSACTIONS on Information
SP - 161
EP - 170
AU - Hitoshi SATOH
AU - Yuji UKAI
AU - Noboru NIKI
AU - Kenji EGUCHI
AU - Kiyoshi MORI
AU - Hironobu OHMATSU
AU - Ryutarou KAKINUMA
AU - Masahiro KANEKO
AU - Noriyuki MORIYAMA
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2001
AB - In this paper, we present a computer-aided diagnosis (CAD) system to automatically detect lung cancer candidates at an early stage using a present and a past helical CT screening. We have developed a slice matching algorithm that can automatically match the slice images of a past CT scan to those of a present CT scan in order to detect changes in the lung fields over time. The slice matching algorithm consists of two main process: the process of extraction of the lungs, heart, and descending aorta and the process of matching slices of the present and past CT images using the information of the lungs, heart, and descending aorta. To evaluate the performance of this algorithm, we applied it to 50 subjects (total of 150 scans) screened between 1993 and 1998. From these scans, we selected 100 pairs for evaluation (each pair consisted of scans for the same subject). The algorithm correctly matched 88 out of the 100 pairs. The slice images for the present and past CT scans are displayed in parallel on the CRT monitor. Feature measurements of the suspicious regions are shown on the relevant images to facilitate identification of changes in size, shape, and intensity. The experimental results indicate that the CAD system can be effectively used in clinical practice to increase the speed and accuracy of routine diagnosis.
ER -