TY - GEN
T1 - Image analysis for neuroblastoma classification
T2 - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
AU - Gurcan, Metin N.
AU - Pan, Tony
AU - Shimada, Hiro
AU - Saltz, Joel
PY - 2006
Y1 - 2006
N2 - Neuroblastoma is a childhood cancer of the nervous system. Current prognostic classification of this disease partly relies on morphological characteristics of the cells from H&E-stained images. In this work, an automated cell nuclei segmentation method is developed. This method employs morphological top-hat by reconstruction algorithm coupled with hysteresis thresholding to both detect and segment the cell nuclei. Accuracy of the automated cell nuclei segmentation algorithm is measured by comparing its outputs to manual segmentation. The average segmentation accuracy is 90.24±5.14%.
AB - Neuroblastoma is a childhood cancer of the nervous system. Current prognostic classification of this disease partly relies on morphological characteristics of the cells from H&E-stained images. In this work, an automated cell nuclei segmentation method is developed. This method employs morphological top-hat by reconstruction algorithm coupled with hysteresis thresholding to both detect and segment the cell nuclei. Accuracy of the automated cell nuclei segmentation algorithm is measured by comparing its outputs to manual segmentation. The average segmentation accuracy is 90.24±5.14%.
UR - https://www.scopus.com/pages/publications/34047155070
U2 - 10.1109/IEMBS.2006.260837
DO - 10.1109/IEMBS.2006.260837
M3 - Conference contribution
C2 - 17947119
SN - 1424400325
SN - 9781424400324
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 4844
EP - 4847
BT - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Y2 - 30 August 2006 through 3 September 2006
ER -