Digital Image Processing
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
The Advantages of Landscape Neutrality in Digital Circuit Evolution
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
Proceedings of the European Conference on Genetic Programming
Neutrality and the Evolvability of Boolean Function Landscape
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
A multi-chromosome approach to standard and embedded cartesian genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Parallel evolution using multi-chromosome cartesian genetic programming
Genetic Programming and Evolvable Machines
Redundancy and computational efficiency in Cartesian genetic programming
IEEE Transactions on Evolutionary Computation
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Mammograms are high resolution x-rays of the breast that are widely used to screen for cancer in women. This paper describes the first stage of development of a novel representation of Cartesian Genetic Programming as part of a computer aided diagnostic system. Specifically, this work is concerned with automated recognition of microcalcifications, one of the key structures used to identify cancer. Results are presented for the application of the proposed algorithm to a number of mammogram sections taken from the Lawrence Livermore National Laboratory database. These demonstrate the proposed representation is effective in locating microcalcifications and will provide a promising basis on which to conduct future work in discriminating between microcalcifications that are indicative of cancer and those that are not.