The present application relates to the field of health care
information technology, and in particular to a
primary liver cancer postoperative micro-
metastasis detection method based on multispectral
molecular imaging. A high-frequency echo proportion map is constructed by means of an undetected
radio frequency signal, and a
liver parenchyma region is segmented to exclude scar interference; a pulsation amplitude map is extracted by means of a multispectral photoacoustic
time sequence image, and the phase is corrected in speed by means of the high-frequency echo proportion map to eliminate speed
distortion caused by the scar;
background subtraction is performed based on the average drift trend of the
liver parenchyma region to generate a net
signal enhancement map; a
negative correlation linear model of the pulsation amplitude and the net
signal is fitted in the
liver parenchyma, and the residual is calculated to represent metabolic clearance abnormalities; the residual and the corrected
phase map are weighted and fused to generate a supply and demand imbalance index, and accordingly, an abnormal region is adaptively identified. The method effectively decouples structural artifacts and abnormal regions, and significantly improves detection specificity and positioning accuracy.