Development of the probabilistic neural networkcubic least squares mapping (PNNLSM3) classifier to assess carotid plaques risk
An efficient classification algorithm based on the cubic least squares mapping (LSM3) and the probabilistic neural network (PNN) classifier is proposed for assessing the carotid plaques risk of causing brain infarcts. Ultrasound images of 24 high-risk and 32 low-risk carotid plaques were manually segmented by an experienced physician using a custom developed software. Three textural features, related to the plaques internal composition, the PNN, and the PNNLSM3 classification algorithms were used to design a classification system. PNN classification accuracy was 92.9%, misdiagnosing one high-risk and three low-risk plaques while the PNNLSM3 managed to classify all plaques correctly. The proposed system may be of value to patient management as a second opinion tool, after it is tested on more data in a clinical environment.
probabilistic neural network least squares mapping classification carotid plaque ultrasound