Soft computing approaches to identify cellular quantity of artificial culture bone

This paper describes soft computing identification methods for cellular quantity of Bone Marrow Stromal Cells in artificial culture bones. We attempt to identify cellular quantity with an ultrasonic system and approaches of a neural network and a fuzzy inference. We employ two features; amplitude and frequency. Amplitude is obtained from the raw ultrasonic wave, and frequency is calculated from frequency spectrum obtained by applying cross-spectrum method. A comparison was done with the multi regression method. The neural network approach identifies the cellular quantity with the highest accuracy.