Literature DB >> 20352281

Evaluation of objective similarity measures for selecting similar images of mammographic lesions.

Ryohei Nakayama1, Hiroyuki Abe, Junji Shiraishi, Kunio Doi.   

Abstract

The purpose of this study was to investigate four objective similarity measures as an image retrieval tool for selecting lesions similar to unknown lesions on mammograms. Measures A and B were based on the Euclidean distance in feature space and the psychophysical similarity measure, respectively. Measure C was the sequential combination of B and A, whereas measure D was the sequential combination of A and B. In this study, we selected 100 lesions each for masses and clustered microcalcifications randomly from our database, and we selected five pairs of lesions from 4,950 pairs based on all combinations of the 100 lesions by use of each measure. In two observer studies for 20 mass pairs and 20 calcification pairs, six radiologists compared all combinations of 20 pairs by using a two-alternative forced-choice method to determine the subjective similarity ranking score which was obtained from the frequency with which a pair was considered as more similar than the other 19 pairs. In both mass and calcification pairs, pairs selected by use of measure D had the highest mean value of the average subjective similarity ranking scores. The difference between measures D and A (P = 0.008 and 0.024), as well as that between measures D and B (P = 0.018 and 0.028) were statistically significant for masses and microcalcifications, respectively. The sequential combination of the objective similarity measure based on the Euclidean distance and the psychophysical similarity measure would be useful in the selection of images similar to those of unknown lesions.

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Year:  2011        PMID: 20352281      PMCID: PMC3046795          DOI: 10.1007/s10278-010-9288-3

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


  20 in total

1.  Computer-aided, case-based diagnosis of mammographic regions of interest containing microcalcifications.

Authors:  J Sklansky; E Y Tao; M Bazargan; C J Ornes; R C Murchison; S Teklehaimanot
Journal:  Acad Radiol       Date:  2000-06       Impact factor: 3.173

2.  Example-based assisting approach for pulmonary nodule classification in three-dimensional thoracic computed tomography images.

Authors:  Yoshiki Kawata; Noboru Niki; Hironobu Ohmatsu; Noriyuki Moriyama
Journal:  Acad Radiol       Date:  2003-12       Impact factor: 3.173

3.  Automated storage and retrieval of thin-section CT images to assist diagnosis: system description and preliminary assessment.

Authors:  Alex M Aisen; Lynn S Broderick; Helen Winer-Muram; Carla E Brodley; Avinash C Kak; Christina Pavlopoulou; Jennifer Dy; Chi-Ren Shyu; Alan Marchiori
Journal:  Radiology       Date:  2003-07       Impact factor: 11.105

4.  Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules.

Authors:  Qiang Li; Feng Li; Junji Shiraishi; Shigehiko Katsuragawa; Shusuke Sone; Kunio Doi
Journal:  Med Phys       Date:  2003-10       Impact factor: 4.071

5.  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

6.  A similarity learning approach to content-based image retrieval: application to digital mammography.

Authors:  Issam El-Naqa; Yongyi Yang; Nikolas P Galatsanos; Robert M Nishikawa; Miles N Wernick
Journal:  IEEE Trans Med Imaging       Date:  2004-10       Impact factor: 10.048

7.  Investigation of psychophysical similarity measures for selection of similar images in the diagnosis of clustered microcalcifications on mammograms.

Authors:  Chisako Muramatsu; Qiang Li; Robert Schmidt; Junji Shiraishi; Kunio Doi
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

8.  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

9.  Design methods and architectural issues of integrated medical image data base systems.

Authors:  S T Wong; H K Huang
Journal:  Comput Med Imaging Graph       Date:  1996 Jul-Aug       Impact factor: 4.790

10.  Integrating content-based retrieval in a medical image reference database.

Authors:  G Bucci; S Cagnoni; R De Dominicis
Journal:  Comput Med Imaging Graph       Date:  1996 Jul-Aug       Impact factor: 4.790

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  4 in total

1.  Endowing a Content-Based Medical Image Retrieval System with Perceptual Similarity Using Ensemble Strategy.

Authors:  Marcos Vinicius Naves Bedo; Davi Pereira Dos Santos; Marcelo Ponciano-Silva; Paulo Mazzoncini de Azevedo-Marques; André Ponce de León Ferreira de Carvalho; Caetano Traina
Journal:  J Digit Imaging       Date:  2016-02       Impact factor: 4.056

2.  Content-based image retrieval in radiology: analysis of variability in human perception of similarity.

Authors:  Jessica Faruque; Christopher F Beaulieu; Jarrett Rosenberg; Daniel L Rubin; Dorcas Yao; Sandy Napel
Journal:  J Med Imaging (Bellingham)       Date:  2015-04-03

3.  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

Review 4.  Overview on subjective similarity of images for content-based medical image retrieval.

Authors:  Chisako Muramatsu
Journal:  Radiol Phys Technol       Date:  2018-05-08
  4 in total

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