High resolution of image segment algorithm plays a very important role in biomedical modeling and diagnosis, which is difficult to be easily solved by traditional algorithms. This article presents a biomedical image segment algorithm based on computational intelligence. First, an assessment method for image resolution is proposed here, and some related models are also compared. In addition, the assessment method aims at high resolution, rather than defining a comprehensive model of the human visual system. Second, a high resolution algorithm is illustrated where the BP neural network is trained from numerical features. The proposed approach permits person to get biomedical model with a high resolution. Third, some experimental results are presented for illustration, and the numerical analysis verifies the resolution measurement and the effectiveness of the BP neural method. Last, some interesting conclusions and future work are indicated at the end of the paper.