Improving image quality around subtle lung nodules by reducing artifacts in similar subtraction imaging

Hitomi Nakamura, Junji Morishita, Yoichiro Shimizu, Yongsu Yoon, Yusuke Matsunobu, Shigehiko Katsuragawa, Hidetake Yabuuchi

Research output: Contribution to journalArticle

Abstract

Similar subtraction imaging is useful for the detection of lung nodules; however, some artifacts on similar subtraction images reduce their utility. The authors attempted to improve the image quality of similar subtraction images by reducing artifacts caused by differences in image contrast and sharpness between two images used for similar subtraction imaging. Image contrast was adjusted using the histogram specification technique. The differences in image sharpness were compensated for using a pixel matching technique. The improvement in image quality was evaluated objectively based on the degree of artifacts and the contrast-to-noise ratio (CNR) of the lung nodules. The artifacts in similar subtraction images were reduced in 94% (17/18) of cases, and CNR was improved in 83% (15/18) of cases. The results indicate that the combination of histogram specification and pixel matching techniques is potentially useful in improving image quality in similar subtraction imaging.

Original languageEnglish
Pages (from-to)460-466
Number of pages7
JournalRadiological physics and technology
Volume11
Issue number4
DOIs
Publication statusPublished - Dec 1 2018

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All Science Journal Classification (ASJC) codes

  • Radiation
  • Physical Therapy, Sports Therapy and Rehabilitation
  • Radiology Nuclear Medicine and imaging

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