COMPUTER-AIDED DETECTION OF CLUSTERED MICROCALCIFICATIONS IN DIGITIZED MAMMOGRAMS

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.