A novel image toggle tool for comparison of serial mammograms: automatic density normalization and alignment-development of the tool and initial experience.

Purpose: The purpose is to develop a new image toggle tool with automatic density normalization (ADN) and automatic alignment (AA) for comparing serial digital mammograms (DMGs).Materials and Methods: We developed an ADN and AA process to compare the images of serial DMGs. In image density normaliza...

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Bibliographic Details
Published in:Japanese Journal of Radiology Vol. 32; no. 12; pp. 725 - 732
Main Authors: Honda, Satoshi, Tsunoda, Hiroko, Fukuda, Wataru, Saida, Yukihisa
Format: research Journal Article
Published: Springer Nature Dec2014
Online Access:View this record in EBSCOhost
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      dt: Dec2014
      vid: 32
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      pub: Springer Nature
      place: New York, New York
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        2012844891
        10.1007/s11604-014-0362-5
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        atl: A novel image toggle tool for comparison of serial mammograms: automatic density normalization and alignment-development of the tool and initial experience.
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          Honda, Satoshi
          Tsunoda, Hiroko
          Fukuda, Wataru
          Saida, Yukihisa
      sug:
        subj:
          Breast Neoplasms Radiography
          Mammography Methods
          Radiographic Image Enhancement Methods
          Radiographic Image Interpretation, Computer-Assisted Methods
          Algorithms
          Female
          Human
          Retrospective Design
          Female
      ab: Purpose: The purpose is to develop a new image toggle tool with automatic density normalization (ADN) and automatic alignment (AA) for comparing serial digital mammograms (DMGs).Materials and Methods: We developed an ADN and AA process to compare the images of serial DMGs. In image density normalization, a linear interpolation was applied by taking two points of high- and low-brightness areas. The alignment was calculated by determining the point of the greatest correlation while shifting the alignment between the current and prior images. These processes were performed on a PC with a 3.20-GHz Xeon processor and 8 GB of main memory. We selected 12 suspected breast cancer patients who had undergone screening DMGs in the past. Automatic processing was retrospectively performed on these images. Two radiologists subjectively evaluated them.Results: The process of the developed algorithm took approximately 1 s per image. In our preliminary experience, two images could not be aligned approximately. When they were aligned, image toggling allowed detection of differences between examinations easily.Conclusions: We developed a new tool to facilitate comparative reading of DMGs on a mammography viewing system. Using this tool for toggling comparisons might improve the interpretation efficiency of serial DMGs.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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