TY - GEN
T1 - Diagnosis of cervical cancer using the median M-type radial basis function (MMRBF) neural network
AU - Gómez-Mayorga, Margarita E.
AU - Gallegos-Funes, Francisco J.
AU - De-La-Rosa-Vázquez, José M.
AU - Cruz-Santiago, Rene
AU - Ponomaryov, Volodymyr
PY - 2009
Y1 - 2009
N2 - The automatic analysis of Pap smear microscopic images is one of the most interesting fields in biomedical image processing. In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) neural network in the classification of cervical cancer cells. From simulation results we observe that the MMRBF neural network has better classification capabilities in comparison with the Median RBF algorithm used as comparative.
AB - The automatic analysis of Pap smear microscopic images is one of the most interesting fields in biomedical image processing. In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) neural network in the classification of cervical cancer cells. From simulation results we observe that the MMRBF neural network has better classification capabilities in comparison with the Median RBF algorithm used as comparative.
KW - Cervical cancer cell
KW - Median M-type Radial Basis Function neural network
KW - Pap smear
UR - http://www.scopus.com/inward/record.url?scp=70549104990&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-05258-3_23
DO - 10.1007/978-3-642-05258-3_23
M3 - Contribución a la conferencia
SN - 3642052576
SN - 9783642052576
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 258
EP - 267
BT - MICAI 2009
T2 - 8th Mexican International Conference on Artificial Intelligence, MICAI 2009
Y2 - 9 November 2009 through 13 November 2009
ER -