The invention discloses a method for detecting deep venous
thrombosis of a patient with traumatic
craniocerebral injury, and relates to the technical field of deep venous
thrombosis detection. The method comprises the following steps: acquiring
deep vein images and physiological parameters, performing
noise reduction, normalization and abnormal value
elimination, extracting
vein structures and suspected
thrombus features, marking gray scale and morphological anomaly regions, and forming a
feature vector library; analyzing a physiological parameter
time sequence trend, dividing high, medium and low risks, and associating
image analysis; weighting and fusing the image and the physiological parameters, judging a
thrombus area and marking the type, the position and the size; the
thrombus change is manually rechecked and dynamically monitored, and clinical intervention is associated to form a
closed loop; and generating and filing an encrypted report, and
synchronizing the encrypted report to an
electronic medical record system. The thrombus detection comprehensiveness and accuracy are improved through multi-data fusion,
dynamic monitoring and risk pre-judgment are achieved, the
system adapts to clinical scenes, efficient support is provided for thrombus management of traumatic
craniocerebral injury patients, and intervention opportunities and schemes are optimized.