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Autor(en) / Beteiligte
Titel
Image processing can cause some malignant soft-tissue lesions to be missed in digital mammography images
Ist Teil von
  • Clinical radiology, 2017-09, Vol.72 (9), p.799.e1-799.e8
Ort / Verlag
England: Elsevier Ltd
Erscheinungsjahr
2017
Quelle
Access via ScienceDirect (Elsevier)
Beschreibungen/Notizen
  • Aim To investigate the effect of image processing on cancer detection in mammography. Methods and materials An observer study was performed using 349 digital mammography images of women with normal breasts, calcification clusters, or soft-tissue lesions including 191 subtle cancers. Images underwent two types of processing: FlavourA (standard) and FlavourB (added enhancement). Six observers located features in the breast they suspected to be cancerous (4,188 observations). Data were analysed using jackknife alternative free-response receiver operating characteristic (JAFROC) analysis. Characteristics of the cancers detected with each image processing type were investigated. Results For calcifications, the JAFROC figure of merit (FOM) was equal to 0.86 for both types of image processing. For soft-tissue lesions, the JAFROC FOM were better for FlavourA (0.81) than FlavourB (0.78); this difference was significant ( p= 0.001). Using FlavourA a greater number of cancers of all grades and sizes were detected than with FlavourB. FlavourA improved soft-tissue lesion detection in denser breasts ( p= 0.04 when volumetric density was over 7.5%) Conclusions The detection of malignant soft-tissue lesions (which were primarily invasive) was significantly better with FlavourA than FlavourB image processing. This is despite FlavourB having a higher contrast appearance often preferred by radiologists. It is important that clinical choice of image processing is based on objective measures.
Sprache
Englisch
Identifikatoren
ISSN: 0009-9260
eISSN: 1365-229X
DOI: 10.1016/j.crad.2017.03.024
Titel-ID: cdi_proquest_miscellaneous_1893970739

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