This paper proposed a maximum intensity projection method to enhance the depth and shape perception of the internal maximum intensity features, without a sophisticated or time-consuming transfer function specification. On the basis of a traditional maximum intensity projection, the study first searched for the boundary sample with a similar intensity value and the optimal normal in front of the maximum intensity feature. Through by comparing the intensity and gradient norm. Next, the local illumination coefficients were updated according to the depth of boundary structures, the consequential depth-based shading results largely enhanced the depth, and the shape perception of internal feasible structures. A two-threshold region growing scheme was designed to perform and further highlight the features of interest. The seed was selected by users interactively on the rendered image, and the growing process depended on the intensity values and 3D spatial distances of the boundary samples with optimal normal. The comparison results showed that the proposed method provided more depth cues and shape information of the maximum intensity features than traditional methods and had practical applications in medical and engineering fields.