PFP-LHCINCA: Pyramidal Fixed-Size Patch-Based Feature Extraction and Chi-Square Iterative Neighborhood Component Analysis for Automated Fetal Sex Classification on Ultrasound Images

Table 5

Comparison of PFP-LHCINCA model with published results of other ultrasound-based fetal sex classification methods.

Study	Method	Dataset	Best accuracy (%)
Maysanjaya et al. [7]	Learning vector quantization, artificial vector quantization	64 males; 25 females	63.0%
Aljuboori et al. [8]	Fuzzy C-mean, discrete wavelet transform, local binary pattern, median, Laplacian filters	50 males; 50 females	94.0%
PFP-LHCINCA	Pyramidal fixed-size patch division, local phase quantization and histogram of oriented gradients based feature extraction, hybrid Chi2 and iterative neighborhood component analysis feature selection	339 males; 332 females	99.11% (kNN classifier tuned with Bayesian optimizer)