Literature DB >> 19030967

Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings.

Sumiaki Matsumoto1, Yoshiharu Ohno, Hitoshi Yamagata, Daisuke Takenaka, Kazuro Sugimura.   

Abstract

PURPOSE: We have been developing a computer-aided detection (CAD) system for lung nodules on multidetector row computed tomography (MDCT). The scheme for nodule detection in this system is featured by three-dimensional analysis of nodule candidates [corrected] and their surroundings, which is designed to discriminate nodules from blood vessels. The purpose of this study was to evaluate the CAD system.
MATERIALS AND METHODS: MDCT images from 30 patients with lung nodules were read twice, 3 weeks apart by a chest radiologist to detect noncalcified nodules of > or = 4 mm. The first reading was without CAD, and the second reading was with CAD. Based on the reference standard later determined by another chest radiologist, the sensitivity of the former chest radiologist without or with CAD was obtained; the sensitivity and false-positive rate of the system alone were also obtained.
RESULTS: The reference standard consisted of 66 nodules. The sensitivity of the chest radiologist was 77% (51/66) without CAD and 91% (60/66) with CAD, showing a significant improvement. The CAD system alone showed a sensitivity of 79% (52/66) with the false-positive rate of 4.5 per patient.
CONCLUSION: Although preliminary, these results indicate the efficacy of the CAD system.

Entities:  

Mesh:

Year:  2008        PMID: 19030967     DOI: 10.1007/s11604-008-0272-5

Source DB:  PubMed          Journal:  Radiat Med        ISSN: 0288-2043


  21 in total

Review 1.  Computer-aided diagnosis of small pulmonary nodules.

Authors:  A P Reeves; W J Kostis
Journal:  Semin Ultrasound CT MR       Date:  2000-04       Impact factor: 1.875

2.  Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images.

Authors:  S Hu; E A Hoffman; J M Reinhardt
Journal:  IEEE Trans Med Imaging       Date:  2001-06       Impact factor: 10.048

3.  Automated detection of lung nodules in CT scans: preliminary results.

Authors:  S G Armato; M L Giger; H MacMahon
Journal:  Med Phys       Date:  2001-08       Impact factor: 4.071

4.  Lung micronodules: automated method for detection at thin-section CT--initial experience.

Authors:  Matthew S Brown; Jonathan G Goldin; Robert D Suh; Michael F McNitt-Gray; James W Sayre; Denise R Aberle
Journal:  Radiology       Date:  2003-01       Impact factor: 11.105

5.  The potential contribution of a computer-aided detection system for lung nodule detection in multidetector row computed tomography.

Authors:  Jeong Won Lee; Jin Mo Goo; Hyun Ju Lee; Jong Hyo Kim; Seunghwan Kim; Youn Tae Kim
Journal:  Invest Radiol       Date:  2004-11       Impact factor: 6.016

6.  Feature subset selection for improving the performance of false positive reduction in lung nodule CAD.

Authors:  Lilla Böröczky; Luyin Zhao; K P Lee
Journal:  IEEE Trans Inf Technol Biomed       Date:  2006-07

7.  Computer-aided diagnosis for pulmonary nodules based on helical CT images.

Authors:  K Kanazawa; Y Kawata; N Niki; H Satoh; H Ohmatsu; R Kakinuma; M Kaneko; N Moriyama; K Eguchi
Journal:  Comput Med Imaging Graph       Date:  1998 Mar-Apr       Impact factor: 4.790

8.  Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society.

Authors:  J H Austin; N L Müller; P J Friedman; D M Hansell; D P Naidich; M Remy-Jardin; W R Webb; E A Zerhouni
Journal:  Radiology       Date:  1996-08       Impact factor: 11.105

9.  Computerized detection of pulmonary nodules in computed tomography images.

Authors:  M L Giger; K T Bae; H MacMahon
Journal:  Invest Radiol       Date:  1994-04       Impact factor: 6.016

10.  CT reconstruction algorithm selection in the evaluation of solitary pulmonary nodules.

Authors:  S J Swensen; R L Morin; G L Aughenbaugh; D W Leimer
Journal:  J Comput Assist Tomogr       Date:  1995 Nov-Dec       Impact factor: 1.826

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  3 in total

1.  Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter.

Authors:  Atsushi Teramoto; Hiroshi Fujita
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-06-09       Impact factor: 2.924

2.  Combination of computer-aided detection algorithms for automatic lung nodule identification.

Authors:  Niccolò Camarlinghi; Ilaria Gori; Alessandra Retico; Roberto Bellotti; Paolo Bosco; Piergiorgio Cerello; Gianfranco Gargano; Ernesto Lopez Torres; Rosario Megna; Marco Peccarisi; Maria Evelina Fantacci
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-07-08       Impact factor: 2.924

3.  Large scale validation of the M5L lung CAD on heterogeneous CT datasets.

Authors:  E Lopez Torres; E Fiorina; F Pennazio; C Peroni; M Saletta; N Camarlinghi; M E Fantacci; P Cerello
Journal:  Med Phys       Date:  2015-04       Impact factor: 4.071

  3 in total

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