Abstract: A multi-neural net imaging apparatus and method for classification of image elements, such as biological particles. The multi-net structure utilizes subgroups of particle features to partition the decision space by an attribute or physical characteristic of the particle and/or by individual and group particle classification that includes an unknown category. Preprocessing and post processing enables heuristic information to be included as part of the decision making process. Preprocessing classifies particles as artifacts based on certain physical characteristics. Post processing enables the use of contextual information either available from other sources or gleaned from the actual decision making process to further process the probability factors and enhance the decisions.

Abstract: A multi-neural net imaging apparatus and method for classification of image elements, such as biological particles. The multi-net structure utilizes subgroups of particle features to partition the decision space by an attribute or physical characteristic of the particle and/or by individual and group particle classification that includes an unknown category. Preprocessing and post processing enables heuristic information to be included as part of the decision making process. Preprocessing classifies particles as artifacts based on certain physical characteristics. Post processing enables the use of contextual information either available from other sources or gleaned from the actual decision making process to further process the probability factors and enhance the decisions.