The invention relates to an auxiliary
image segmentation method for
bronchoscopy, and relates to the field of medical
image processing, and the method comprises the steps: carrying out the significant feature analysis of an
airway image, and determining a plurality of
airway significant regions; configuring an initial
image segmentation granularity scheme according to the plurality of image saliency degrees; synchronously monitoring and acquiring user physiological features and lens operation features, performing image fuzziness prediction, and generating an
image segmentation compensation coefficient; and adjusting the initial image segmentation
granularity scheme to obtain a corrected image segmentation
granularity scheme, and performing image segmentation on the plurality of
airway salient regions. According to the method, the problems that the requirements of different
lesion areas are difficult to adapt and
false detection or missing detection is easily caused due to the fact that a segmentation strategy cannot be dynamically adjusted according to image features in a traditional method can be solved; according to the method, the segmentation precision and accuracy of the trachea image can be remarkably improved, and efficient and accurate image segmentation is realized, so that different types of
lesion areas can be better identified, and
false detection and missing detection are effectively reduced.