Literature DB >> 2296696

Pulmonary nodules: computer-aided detection in digital chest images.

M L Giger1, K Doi, H MacMahon, C E Metz, F F Yin.   

Abstract

Currently, radiologists fail to detect pulmonary nodules in up to 30% of cases with actually positive findings. Diagnoses may be missed due to camouflaging effects of anatomic background, subjective and varying decision criteria, or distractions in clinical situations. We developed a computerized method to detect locations of lung nodules in digital chest images. The method is based on a difference-image approach and feature-extraction techniques, including growth, slope, and profile tests. Computer results were used to alert 12 radiologists to possible nodule locations in 60 clinical cases. Preliminary results suggest that computer aid can improve the detection performance of radiologists.

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Year:  1990        PMID: 2296696     DOI: 10.1148/radiographics.10.1.2296696

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  12 in total

1.  Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility.

Authors:  S G Armato; M L Giger; H MacMahon
Journal:  J Digit Imaging       Date:  1999-02       Impact factor: 4.056

Review 2.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

3.  Sensitivity and specificity of a CAD solution for lung nodule detection on chest radiograph with CTA correlation.

Authors:  William Moore; Jennifer Ripton-Snyder; George Wu; Craig Hendler
Journal:  J Digit Imaging       Date:  2011-06       Impact factor: 4.056

4.  Voice-activated retrieval of mammography reference images.

Authors:  H A Swett; P G Mutalik; V P Neklesa; L Horvath; C Lee; J Richter; I Tocino; P R Fisher
Journal:  J Digit Imaging       Date:  1998-05       Impact factor: 4.056

Review 5.  Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

Authors:  Feng Li
Journal:  Radiol Phys Technol       Date:  2015-05-17

6.  Interval lung cancers not detected on screening chest X-rays: How are they different?

Authors:  Paul A Kvale; Christine Cole Johnson; Martin Tammemägi; Pamela M Marcus; Carl J Zylak; David L Spizarny; William Hocking; Martin Oken; John Commins; Lawrence Ragard; Ping Hu; Christine Berg; Philip Prorok
Journal:  Lung Cancer       Date:  2014-07-24       Impact factor: 5.705

7.  Biplane correlation imaging: a feasibility study based on phantom and human data.

Authors:  Ehsan Samei; Nariman Majdi-Nasab; James T Dobbins; H Page McAdams
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

8.  Differentiation between nodules and end-on vessels using a convolution neural network architecture.

Authors:  J S Lin; A Hasegawa; M T Freedman; S K Mun
Journal:  J Digit Imaging       Date:  1995-08       Impact factor: 4.056

9.  Detection of lung nodules in digital chest radiographs using artificial neural networks: a pilot study.

Authors:  Y C Wu; K Doi; M L Giger
Journal:  J Digit Imaging       Date:  1995-05       Impact factor: 4.056

Review 10.  Potential usefulness of digital imaging in clinical diagnostic radiology: computer-aided diagnosis.

Authors:  K Doi; M L Giger; R M Nishikawa; K R Hoffmann; H MacMahon; R A Schmidt
Journal:  J Digit Imaging       Date:  1995-02       Impact factor: 4.056

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