Computer-aided detection of clustered microcalcifications in digitized mammograms

Abstract

Rationale and objectives: We investigated a computer-aided detection (CAD) scheme for clustered microcalcifications in digitized mammograms.

Methods: A multistage CAD scheme was developed and tested. To increase sensitivity, the scheme uses a Gaussian band-pass filter and nonlinear threshold. A multistage local minimum searching routine and a multilayer topographic feature analysis are used to reduce the false-positive detection rate. One hundred ten digitized mammograms were used in this preliminary test, with 55 images containing one or two verified microcalcification clusters.

Results: The CAD scheme achieved 100% sensitivity and had an average false-positive detection rate of 0.18 per image.

Conclusion: The CAD scheme performs as well as many published schemes and has some unique advantages to further improve detection sensitivity and specificity of future CAD schemes.