Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Classifying Cells for Cancer Diagnosis Using Neural Networks
IEEE Expert: Intelligent Systems and Their Applications
Cell Segmentation with Median Filter and Mathematical Morphology Operation
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Thyroid Cancer Cells Boundary Location by a Fuzzy Edge Detection Method
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
MIAR '01 Proceedings of the International Workshop on Medical Imaging and Augmented Reality (MIAR '01)
MIAR '01 Proceedings of the International Workshop on Medical Imaging and Augmented Reality (MIAR '01)
Computer-aided detection of breast cancer nuclei
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Non-uniform cellular automata based associative memory: Evolutionary design and basins of attraction
Information Sciences: an International Journal
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The examination of morphological features is used as a universal procedure by pathologists to determine whether cells are cancerous. Generally speaking, the shapes of normal cells are more standard (either circular or oval) than those of cancerous cells. The objective of this study was to construct an autonomous feature detection system, with the hope of finding some feature patterns, based on morphological shapes (contours), that could be used to separate cancerous cells from normal cells. A number of feature detectors (FDs) were initially generated at random. Then they were modified through evolutionary learning and cellular automata. The experimental result showed that this system was able to search appropriate FDs to identify cancerous cells in a self-organizing manner. It also showed that these FDs were general so that each of them could be used to identify more than one cancerous cell, and that there existed some common patterns of cell deformity among cancerous cells. This system was also applied to two other domains, and achieved satisfactory experimental results.