The invention relates to the technical field of abdominal
lymph node partitioning, in particular to an abdominal
lymph node partitioning method based on an attention mechanism neural network. The abdominal
lymph node partitioning method based on the attention mechanism neural network is used for solving the problems that in the prior art, a doctor has a large difference in film reading results ofthe same
abdominal CT medical image, and prediction of abdominal
lymph node partitioning is inaccurate. The method comprises the following steps: step 1, preparing data; step 2, generating a
mask, andpreprocessing the data; step 3, constructing an attention mechanism residual
network model; step 4, repeating the step 3, and constructing and training a model of
lymph node relative position partitioning; and step 5, classifying the abdominal lymph nodes automatically detected by the detection task by using the model trained in the step 3 and the step 4. According to the method, the original CTimage and the
mask are overlapped to serve as input, and the attention mechanism is introduced into the deep
residual neural network, so that the abdominal lymph nodes in the CT image can be accurately partitioned.