The invention discloses a contusive retina internal segment / external segment deficiency three-dimensional automatic detecting method based on an SD-OCT image. The method comprises the following steps that (1), an image is preprocessed, wherein the interior of the retina is automatically divided into eleven surfaces through a multi-scale three-dimensional image division method, an internal segment / external segment area between the seventh surface and the eighth surface is extracted as an area of interest, and planarization processing and bilinear filtering enhancement are carried out; (2), five classes (fifty-seven in total) of features are extracted from each voxel in the area of interest; (3), the features are optimized and selected through a principal component analysis method; (4), the feature samples are classified to be a training set and a testing set, and the samples of the training set are trained and integrated to be a classifier through an Adaboost algorithm; (5), deficiency / non-deficiency identification is carried out on the samples of the testing set; (6), postprocessing such as vascular contour influence elimination and isolated point elimination are carried out on an identification result, the corresponding deficiency size is calculated, the identification errors of the deficiency size are small, and accuracy is good.