Computer enhancement of mammograms for assistance in detection of microcalcifications

Abstract

At current rate of incidence, breast cancer will afflict about 9% of women. Regular mammograms have proven to be effective in early detection of breast cancer. In mammograms the presence of microcalcification clusters is an indicator of breast cancer. However, because of their size they cannot always be detected by visual inspection or reading of mammograms. This work constitutes an attempt towards reducing the difficulty associated with detecting microcalcifications by computer processing of mammograms. Nine features based on textural properties are extracted from previously identified microcalcification areas. Prinicipal component analysis is then employed to obtain the five most invariant feature projection components. These features are then fed into a new clustering algorithm called Interactive Selective and Adaptive Clustering (Issac), which identifies areas with a high confidence of microcalcification presence. This algorithm selectively rejects overly sensitive samples based on the number of neighboring samples in the feature space. The algorithm adapts the feature space to reject false positives and accept true negatives as the radiologist graphically identifies them. A set of heuristics called Interactive Selective and Integral Adaptive Heuristics (Isaiah) were developed to provide Issac stronger selection power. Three radiologists were asked to rate the level of assistance provided by the above computer program in identifying microcalcifications. The scale of computer assistance was considered to be between 0 and 10 with 10 reflecting the highest assistance level. The radiologists appreciated the developed computer assisted tool as a practical means of quickly identifying suspicious microcalcification areas easily missed during a routine clinical reading procedure. All the algorithms are incorporated into a PC Windows-based graphical-user-interface (GUI) allowing radiologists with little training to easily manipulate mammograms for the identification of microcalcifications.