Contrast enhancement in dense breast images to aid clustered microcalcifications detection.

This paper presents a method to provide contrast enhancement in dense breast digitized images, which are difficult cases in testing of computer-aided diagnosis (CAD) schemes. Three techniques were developed, and data from each method were combined to provide a better result in relation to detection...

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Publicado en:Journal of Digital Imaging Vol. 20; no. 1; pp. 53 - 67
Autores principales: Nunes FLS, Schiabel H, Goes CE
Formato: equations & formulas tables/charts Journal Article
Publicado: Springer Nature Mar2007
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2007
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      pub: Springer Nature
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        atl: Contrast enhancement in dense breast images to aid clustered microcalcifications detection.
      aug:
        au:
          Nunes FLS
          Schiabel H
          Goes CE
        affil: Programa de Pós-Graduaçao em Ciência da Computaçao, Centro Universitário Eurípides de Marília, Av. Hygino Muzzi Filho, 529-Campus Universitário, 17525-901, Marília, SP, Brazil.
      sug:
        subj:
          Breast Radiography
          Diagnosis, Computer Assisted
          Image Processing, Computer Assisted Methods
          Radiography, Computed
          Breast Anatomy and Histology
          Calcinosis
          Contrast Media
          False Negative Results
          False Positive Results
          Mammography
          ROC Curve
      ab: This paper presents a method to provide contrast enhancement in dense breast digitized images, which are difficult cases in testing of computer-aided diagnosis (CAD) schemes. Three techniques were developed, and data from each method were combined to provide a better result in relation to detection of clustered microcalcifications. Results obtained during the tests indicated that, by combining all the developed techniques, it is possible to improve the performance of a processing scheme designed to detect microcalcification clusters. It also allows operators to distinguish some of these structures in low-contrast images, which were not detected via conventional processing before the contrast enhancement. This investigation shows the possibility of improving CAD schemes for better detection of microcalcifications in dense breast images.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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