Literature DB >> 14669062

Computer-assisted detection of pulmonary nodules: preliminary observations using a prototype system with multidetector-row CT data sets.

Leo P Lawler1, Susan A Wood, Harpreet K Pannu, Elliot K Fishman, Harpreet S Pannu.   

Abstract

The continued revolution in multidetector-row CT (MDCT) scanning increases the quality of lung imaging but at the cost of a greater burden of data for review and interpretation. This article discusses our preliminary experience with prototype software for lung nodule detection and characterization using MDCT data sets. We discuss the potential role of computer-assisted detection (CAD) as applied to the automatic detection of lung nodules. We also review the process of CAD, outline its potential results, and explore how it may fit into existing radiology practice. Finally, we discuss MDCT data-acquisition parameters and how they may affect the performance of CAD.

Mesh:

Year:  2003        PMID: 14669062      PMCID: PMC3045255          DOI: 10.1007/s10278-003-1654-y

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  15 in total

1.  Chest CT: automated nodule detection and assessment of change over time--preliminary experience.

Authors:  J P Ko; M Betke
Journal:  Radiology       Date:  2001-01       Impact factor: 11.105

2.  Computerized detection of pulmonary nodules on CT scans.

Authors:  S G Armato; M L Giger; C J Moran; J T Blackburn; K Doi; H MacMahon
Journal:  Radiographics       Date:  1999 Sep-Oct       Impact factor: 5.333

Review 3.  Lung cancer screening.

Authors:  J R Ellis; F V Gleeson
Journal:  Br J Radiol       Date:  2001-06       Impact factor: 3.039

4.  Multislice helical CT of focal and diffuse lung disease: comprehensive diagnosis with reconstruction of contiguous and high-resolution CT sections from a single thin-collimation scan.

Authors:  U J Schoepf; R D Bruening; C Hong; R Eibel; S Aydemir; A Crispin; C Becker; M F Reiser
Journal:  AJR Am J Roentgenol       Date:  2001-07       Impact factor: 3.959

Review 5.  Ten criteria for effective screening: their application to multislice CT screening for pulmonary and colorectal cancers.

Authors:  N A Obuchowski; R J Graham; M E Baker; K A Powell
Journal:  AJR Am J Roentgenol       Date:  2001-06       Impact factor: 3.959

6.  Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation.

Authors:  D F Yankelevitz; A P Reeves; W J Kostis; B Zhao; C I Henschke
Journal:  Radiology       Date:  2000-10       Impact factor: 11.105

7.  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

8.  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

9.  Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center.

Authors:  T W Freer; M J Ulissey
Journal:  Radiology       Date:  2001-09       Impact factor: 11.105

Review 10.  A consensus statement of the Society of Thoracic Radiology: screening for lung cancer with helical computed tomography.

Authors:  D R Aberle; G Gamsu; C I Henschke; D P Naidich; S J Swensen
Journal:  J Thorac Imaging       Date:  2001-01       Impact factor: 3.000

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  3 in total

1.  Detection of small pulmonary nodules in high-field MR at 3 T: evaluation of different pulse sequences using porcine lung explants.

Authors:  M Regier; S Kandel; M G Kaul; B Hoffmann; H Ittrich; P M Bansmann; J Kemper; C Nolte-Ernsting; M Heller; G Adam; J Biederer
Journal:  Eur Radiol       Date:  2006-09-30       Impact factor: 5.315

Review 2.  Recent progress in computer-aided diagnosis of lung nodules on thin-section CT.

Authors:  Qiang Li
Journal:  Comput Med Imaging Graph       Date:  2007-03-21       Impact factor: 4.790

3.  Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier.

Authors:  Qiang Li; Feng Li; Kunio Doi
Journal:  Acad Radiol       Date:  2008-02       Impact factor: 3.173

  3 in total

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