Literature DB >> 15358850

Computer-aided detection in screening mammography: variability in cues.

Jay A Baker1, Joseph Y Lo, David M Delong, Carey E Floyd.   

Abstract

PURPOSE: To evaluate the variability of true-positive and false-positive cues by using a commercially available computer-aided detection (CAD) system for analysis of 50 malignancies in a screening population.
MATERIALS AND METHODS: Fifty breast cancers detected at screening were analyzed by using a commercially available CAD system. Mean patient age was 62.2 years. Each set of mammograms (craniocaudal and mediolateral oblique views) was digitized and analyzed by the CAD system 10 times. One radiologist compared CAD output with the location of the malignancy at mammography and determined whether each lesion was marked accurately in one mammographic view, both views, or neither. Sensitivity and reproducibility of the CAD system were determined for both case- and image-based analysis.
RESULTS: Overall sensitivity of the CAD system when at least one of the two mammographic views was marked correctly (case-base sensitivity) was 82.4%. Sensitivity when each mammographic view was considered separately (image-based sensitivity) was 61.1%. For case-based analysis, variability in true-positive CAD cues was demonstrated for 14 of 50 (28%) cases. For image-based analysis, inconsistency in CAD output was observed in 33 of 100 (33%) mammographic views that contained malignancies detected at screening. However, the CAD system consistently detected 40-43 of the 50 breast cancers in each of the 10 CAD runs. Variability for false-positive marks was significantly greater than that for true-positive marks.
CONCLUSION: Inconsistency was demonstrated for CAD analysis of breast cancers detected at screening. However, the CAD system was reasonably consistent in the overall number of cancers identified from run to run. Greater variability of the CAD system was also demonstrated for false-positive marks, as compared with true-positive marks.

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Year:  2004        PMID: 15358850     DOI: 10.1148/radiol.2332031200

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


  10 in total

1.  Content-based image-retrieval system in chest computed tomography for a solitary pulmonary nodule: method and preliminary experiments.

Authors:  Masahiro Endo; Takeshi Aramaki; Koiku Asakura; Michihisa Moriguchi; Masahiro Akimaru; Akira Osawa; Ryuji Hisanaga; Yoshiyuki Moriya; Kazuo Shimura; Hiroyoshi Furukawa; Ken Yamaguchi
Journal:  Int J Comput Assist Radiol Surg       Date:  2012-01-19       Impact factor: 2.924

2.  Automated segmentation of hepatic vessels in non-contrast X-ray CT images.

Authors:  Suguru Kawajiri; Xiangrong Zhou; Xuejun Zhang; Takeshi Hara; Hiroshi Fujita; Ryujiro Yokoyama; Hiroshi Kondo; Masayuki Kanematsu; Hiroaki Hoshi
Journal:  Radiol Phys Technol       Date:  2008-07-01

Review 3.  CAD for mammography: the technique, results, current role and further developments.

Authors:  Ansgar Malich; Dorothee R Fischer; Joachim Böttcher
Journal:  Eur Radiol       Date:  2006-01-17       Impact factor: 5.315

4.  Evaluation of breast amorphous calcifications by a computer-aided detection system in full-field digital mammography.

Authors:  A M Scaranelo; R Eiada; K Bukhanov; P Crystal
Journal:  Br J Radiol       Date:  2012-05       Impact factor: 3.039

5.  Assessment of performance and reproducibility of applying a content-based image retrieval scheme for classification of breast lesions.

Authors:  Rohith Reddy Gundreddy; Maxine Tan; Yuchen Qiu; Samuel Cheng; Hong Liu; Bin Zheng
Journal:  Med Phys       Date:  2015-07       Impact factor: 4.071

Review 6.  Digital Analysis in Breast Imaging.

Authors:  Giovanna Negrão de Figueiredo; Michael Ingrisch; Eva Maria Fallenberg
Journal:  Breast Care (Basel)       Date:  2019-06-04       Impact factor: 2.860

Review 7.  Advances in computer-aided diagnosis for breast cancer.

Authors:  Lubomir Hadjiiski; Berkman Sahiner; Heang-Ping Chan
Journal:  Curr Opin Obstet Gynecol       Date:  2006-02       Impact factor: 1.927

8.  Detection of breast cancer in asymptomatic and symptomatic groups using computer-aided detection with full-field digital mammography.

Authors:  Chang Suk Park; Na Young Jung; Kijun Kim; Hyun Seouk Jung; Kyung-Myung Sohn; Se Jeong Oh
Journal:  J Breast Cancer       Date:  2013-09-30       Impact factor: 3.588

9.  Reproducibility of computer-aided detection marks in digital mammography.

Authors:  Seung Ja Kim; Woo Kyung Moon; Nariya Cho; Joo Hee Cha; Sun Mi Kim; Jung-Gi Im
Journal:  Korean J Radiol       Date:  2007 May-Jun       Impact factor: 3.500

10.  Variable size computer-aided detection prompts and mammography film reader decisions.

Authors:  Fiona J Gilbert; Susan M Astley; Caroline Rm Boggis; Magnus A McGee; Pamela M Griffiths; Stephen W Duffy; Olorunsola F Agbaje; Maureen Gc Gillan; Mary Wilson; Anil K Jain; Nicola Barr; Ursula M Beetles; Miriam A Griffiths; Jill Johnson; Rita M Roberts; Heather E Deans; Karen A Duncan; Geeta Iyengar
Journal:  Breast Cancer Res       Date:  2008-08-25       Impact factor: 6.466

  10 in total

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