Computer aided detection of prostate cancer using multiwavelength photoacoustic data with convolutional neural network

•Demonstration of the effectiveness of CNN learned features from raw photoacoustic data for prostate tissue characterization.•Raw photoacoustic data is generated from excised prostates of human patients.•Tissue characterization experimentation is done using classifiers with CNN learned features and raw photoacoustic features.•Results suggest that CNN based classifiers performed better than the classifiers applied with raw photoacoustic features.