Literature DB >> 20054606

Presentation of similar images as a reference for distinction between benign and malignant masses on mammograms: analysis of initial observer study.

Chisako Muramatsu1, Robert A Schmidt, Junji Shiraishi, Qiang Li, Kunio Doi.   

Abstract

The effect of the presentation of similar images for distinction between benign and malignant masses on mammograms was evaluated in the observer performance study. Images of masses were obtained from the Digital Database for Screening Mammography. We selected 50 benign and 50 malignant masses by a stratified randomization method. For each case, similar images were selected based on the size of masses and the similarity measures. Radiologists were shown images with unknown masses and asked to provide their confidence level that the lesions were malignant before and after the presentation of the similar images. Eleven observers, including three attending breast radiologists, three breast imaging fellows, and five residents, participated. The average areas under the receiver operating characteristic curves without and with the presentation of the similar images were almost equivalent. However, there were many cases in which the similar images caused beneficial effects to the observers, whereas there were a small number of cases in which the similar images had detrimental effects. From a detailed analysis of the reasons for these detrimental effects, we found that the similar images would not be useful for diagnosis of rare and very difficult cases, i.e., benign-looking malignant and malignant-looking benign cases. In addition, these cases should not be included in the reference database, because radiologists would be confused by these unusual cases. The results of this study could be very important and useful for the future development and improvement of a computer-aided diagnosis system.

Mesh:

Year:  2010        PMID: 20054606      PMCID: PMC3046675          DOI: 10.1007/s10278-009-9263-z

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


  22 in total

1.  Improvement of radiologists' characterization of mammographic masses by using computer-aided diagnosis: an ROC study.

Authors:  H P Chan; B Sahiner; M A Helvie; N Petrick; M A Roubidoux; T E Wilson; D D Adler; C Paramagul; J S Newman; S Sanjay-Gopal
Journal:  Radiology       Date:  1999-09       Impact factor: 11.105

2.  Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method.

Authors:  D D Dorfman; K S Berbaum; C E Metz
Journal:  Invest Radiol       Date:  1992-09       Impact factor: 6.016

3.  Expert system-controlled image display.

Authors:  H A Swett; P R Fisher; A I Cohn; P L Miller; P G Mutalik
Journal:  Radiology       Date:  1989-08       Impact factor: 11.105

4.  Investigation of psychophysical measure for evaluation of similar images for mammographic masses: preliminary results.

Authors:  Chisako Muramatsu; Qiang Li; Kenji Suzuki; Robert A Schmidt; Junji Shiraishi; Gillian M Newstead; Kunio Doi
Journal:  Med Phys       Date:  2005-07       Impact factor: 4.071

Review 5.  Current status and future potential of computer-aided diagnosis in medical imaging.

Authors:  K Doi
Journal:  Br J Radiol       Date:  2005       Impact factor: 3.039

6.  Classification of breast lesions with multimodality computer-aided diagnosis: observer study results on an independent clinical data set.

Authors:  Karla Horsch; Maryellen L Giger; Carl J Vyborny; Li Lan; Ellen B Mendelson; R Edward Hendrick
Journal:  Radiology       Date:  2006-08       Impact factor: 11.105

7.  A method to improve visual similarity of breast masses for an interactive computer-aided diagnosis environment.

Authors:  Bin Zheng; Amy Lu; Lara A Hardesty; Jules H Sumkin; Christiane M Hakim; Marie A Ganott; David Gur
Journal:  Med Phys       Date:  2006-01       Impact factor: 4.071

Review 8.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

9.  Improving breast cancer diagnosis with computer-aided diagnosis.

Authors:  Y Jiang; R M Nishikawa; R A Schmidt; C E Metz; M L Giger; K Doi
Journal:  Acad Radiol       Date:  1999-01       Impact factor: 3.173

10.  Performance benchmarks for diagnostic mammography.

Authors:  Edward A Sickles; Diana L Miglioretti; Rachel Ballard-Barbash; Berta M Geller; Jessica W T Leung; Robert D Rosenberg; Rebecca Smith-Bindman; Bonnie C Yankaskas
Journal:  Radiology       Date:  2005-06       Impact factor: 11.105

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  5 in total

1.  Modeling perceptual similarity measures in CT images of focal liver lesions.

Authors:  Jessica Faruque; Daniel L Rubin; Christopher F Beaulieu; Sandy Napel
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

2.  Usefulness of presentation of similar images in the diagnosis of breast masses on mammograms: comparison of observer performances in Japan and the USA.

Authors:  Chisako Muramatsu; Robert A Schmidt; Junji Shiraishi; Tokiko Endo; Hiroshi Fujita; Kunio Doi
Journal:  Radiol Phys Technol       Date:  2012-08-08

3.  Computerized determination scheme for histological classification of breast mass using objective features corresponding to clinicians' subjective impressions on ultrasonographic images.

Authors:  Akiyoshi Hizukuri; Ryohei Nakayama; Yumi Kashikura; Haruhiko Takase; Hiroharu Kawanaka; Tomoko Ogawa; Shinji Tsuruoka
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

Review 4.  Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting.

Authors:  Thaworn Dendumrongsup; Andrew A Plumb; Steve Halligan; Thomas R Fanshawe; Douglas G Altman; Susan Mallett
Journal:  PLoS One       Date:  2014-12-26       Impact factor: 3.240

5.  Computer-aided beam arrangement based on similar cases in radiation treatment-planning databases for stereotactic lung radiation therapy.

Authors:  Taiki Magome; Hidetaka Arimura; Yoshiyuki Shioyama; Asumi Mizoguchi; Chiaki Tokunaga; Katsumasa Nakamura; Hiroshi Honda; Masafumi Ohki; Fukai Toyofuku; Hideki Hirata
Journal:  J Radiat Res       Date:  2012-12-18       Impact factor: 2.724

  5 in total

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