Photoacoustic tomography reconstruction using lag-based delay multiply and sum with coherence factor improves in vivo ovarian cancer diagnosis

Among women, ovarian cancer is fifth most common cause of death due to cancer. In clinical ovarian cancer diagnosis via photoacoustic tomography, we face several challenges such as poor image resolution and signal-to-noise ratio (SNR). To address these concerns, we proposed a novel beamformer named lag-based delay multiply and sum combined with coherent factor (DMAS_LAG_CF). The simulations, phantom experiments and ovarian cancer patient data have demonstrated that compared with the delay and sum algorithm (DAS), the new algorithm can achieve better resolution, SNR, and improved hemoglobin contrast of malignant vs. benign ovarian lesions.