Computer-aided diagnostic models in breast cancer screening

Turgay Ayer, Mehmet Us Ayvaci, Ze Xiu Liu, Oguzhan Alagoz, Elizabeth S. Burnside

Research output: Contribution to journalReview articlepeer-review

36 Scopus citations

Abstract

Mammography is the most common modality for breast cancer detection and diagnosis and is often complemented by ultrasound and MRI. However, similarities between early signs of breast cancer and normal structures in these images make detection and diagnosis of breast cancer a difficult task. To aid physicians in detection and diagnosis, computer-aided detection and computer-aided diagnostic (CADx) models have been proposed. A large number of studies have been published for both computer-aided detection and CADx models in the last 20 years. The purpose of this article is to provide a comprehensive survey of the CADx models that have been proposed to aid in mammography, ultrasound and MRI interpretation. We summarize the noteworthy studies according to the screening modality they consider and describe the type of computer model, input data size, feature selection method, input feature type, reference standard and performance measures for each study. We also list the limitations of the existing CADx models and provide several possible future research directions.

Original languageEnglish (US)
Pages (from-to)313-323
Number of pages11
JournalImaging in Medicine
Volume2
Issue number3
DOIs
StatePublished - Jun 1 2010
Externally publishedYes

Keywords

  • breast cancer
  • computer-aided detection
  • computer-aided diagnosis
  • mammography
  • MRI
  • ultrasound

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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