Literature DB >> 12832587

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

Alex M Aisen1, Lynn S Broderick, Helen Winer-Muram, Carla E Brodley, Avinash C Kak, Christina Pavlopoulou, Jennifer Dy, Chi-Ren Shyu, Alan Marchiori.   

Abstract

A software system and database for computer-aided diagnosis with thin-section computed tomographic (CT) images of the chest was designed and implemented. When presented with an unknown query image, the system uses pattern recognition to retrieve visually similar images with known diagnoses from the database. A preliminary validation trial was conducted with 11 volunteers who were asked to select the best diagnosis for a series of test images, with and without software assistance. The percentage of correct answers increased from 29% to 62% with computer assistance. This finding suggests that this system may be useful for computer-assisted diagnosis.

Mesh:

Year:  2003        PMID: 12832587     DOI: 10.1148/radiol.2281020126

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


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

Authors:  Ryohei Nakayama; Hiroyuki Abe; Junji Shiraishi; Kunio Doi
Journal:  J Digit Imaging       Date:  2011-02       Impact factor: 4.056

3.  Comparative performance analysis of state-of-the-art classification algorithms applied to lung tissue categorization.

Authors:  Adrien Depeursinge; Jimison Iavindrasana; Asmâa Hidki; Gilles Cohen; Antoine Geissbuhler; Alexandra Platon; Pierre-Alexandre Poletti; Henning Müller
Journal:  J Digit Imaging       Date:  2008-11-04       Impact factor: 4.056

Review 4.  Content-based medical image retrieval: a survey of applications to multidimensional and multimodality data.

Authors:  Ashnil Kumar; Jinman Kim; Weidong Cai; Michael Fulham; Dagan Feng
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

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

Authors:  Chisako Muramatsu; Robert A Schmidt; Junji Shiraishi; Qiang Li; Kunio Doi
Journal:  J Digit Imaging       Date:  2010-01-07       Impact factor: 4.056

6.  Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis.

Authors:  Petra Welter; Jörg Riesmeier; Benedikt Fischer; Christoph Grouls; Christiane Kuhl; Thomas M Deserno
Journal:  J Am Med Inform Assoc       Date:  2011 Jul-Aug       Impact factor: 4.497

7.  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

8.  Representation of lesion similarity by use of multidimensional scaling for breast masses on mammograms.

Authors:  Chisako Muramatsu; Kohei Nishimura; Tokiko Endo; Mikinao Oiwa; Misaki Shiraiwa; Kunio Doi; Hiroshi Fujita
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

9.  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

10.  Effectiveness of Global Features for Automatic Medical Image Classification and Retrieval - the experiences of OHSU at ImageCLEFmed.

Authors:  Jayashree Kalpathy-Cramer; William Hersh
Journal:  Pattern Recognit Lett       Date:  2008-11-01       Impact factor: 3.756

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