This study proposes a custom optimized convolutional neural network (CO-CNN) for early classification of liver lesions. The approach includes median filtering, Random Forest-based liver extraction, and GLRLM feature extraction before CO-CNN classification. Experimental results demonstrated superior accuracy (97.77%) and sensitivity (96%) compared to existing methods, highlighting its effectiveness for reliable liver tumor classification using perceptual datasets.