Literature DB >> 15955862

Pulmonary nodules: automated detection on CT images with morphologic matching algorithm--preliminary results.

Kyongtae T Bae1, Jin-Sung Kim, Yong-Hum Na, Kwang Gi Kim, Jin-Hwan Kim.   

Abstract

Institutional review board approval was obtained. Informed patient consent was not required for this retrospective study, which involved review of previously obtained image data. Patient confidentiality was protected; the study was compliant with the Health Insurance Portability and Accountability Act. An automated pulmonary nodule detection program that takes advantage of three-dimensional volumetric data was developed and tested with multi-detector row computed tomographic (CT) images from 20 patients (13 men, seven women; age range, 40-75 years) with pulmonary nodules. A total of 164 nodules 3 mm in diameter and larger were detected by two radiologists in consensus and were used as a reference standard to evaluate the computer-aided detection (CAD) program. The CAD algorithm was structured to process nodules that were categorized into three types: isolated, juxtapleural, and juxtavascular. Overall sensitivity for nodule detection with the CAD program was 95.1% (156 of 164 nodules). The sensitivity according to nodule size was 91.2% (52 of 57 nodules) for nodules 3 mm to less than 5 mm and 97.2% (104 of 107 nodules) for nodules 5 mm and larger. The number of false-positive detections per patient was 6.9 for false nodule structures 3 mm and larger and 4.0 for false nodule structures 5 mm and larger. Copyright RSNA, 2005

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Year:  2005        PMID: 15955862     DOI: 10.1148/radiol.2361041286

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  22 in total

1.  An adaptive window-setting scheme for segmentation of bladder tumor surface via MR cystography.

Authors:  Chaijie Duan; Kehong Yuan; Fanghua Liu; Ping Xiao; Guoqing Lv; Zhengrong Liang
Journal:  IEEE Trans Inf Technol Biomed       Date:  2012-05-22

2.  Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.

Authors:  Ted W Way; Lubomir M Hadjiiski; Berkman Sahiner; Heang-Ping Chan; Philip N Cascade; Ella A Kazerooni; Naama Bogot; Chuan Zhou
Journal:  Med Phys       Date:  2006-07       Impact factor: 4.071

Review 3.  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

4.  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

Review 5.  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

6.  High performance lung nodule detection schemes in CT using local and global information.

Authors:  Wei Guo; Qiang Li
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

7.  Multi slice computed tomography in the study of pulmonary metastases.

Authors:  G Angelelli; V Grimaldi; F Spinelli; A Scardapane; A Sardaro
Journal:  Radiol Med       Date:  2008-09-08       Impact factor: 3.469

8.  Adaptive border marching algorithm: automatic lung segmentation on chest CT images.

Authors:  Jiantao Pu; Justus Roos; Chin A Yi; Sandy Napel; Geoffrey D Rubin; David S Paik
Journal:  Comput Med Imaging Graph       Date:  2008-06-02       Impact factor: 4.790

Review 9.  Computer-aided diagnosis of lung cancer and pulmonary embolism in computed tomography-a review.

Authors:  Heang-Ping Chan; Lubomir Hadjiiski; Chuan Zhou; Berkman Sahiner
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

10.  Pulmonary lobe segmentation in CT examinations using implicit surface fitting.

Authors:  Jiantao Pu; Bin Zheng; Joseph K Leader; Carl Fuhrman; Friedrich Knollmann; Amy Klym; David Gur
Journal:  IEEE Trans Med Imaging       Date:  2009-07-21       Impact factor: 10.048

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