Morphological structures such as the optic disc and macula have been extensively utilized in automatic diagnosis and screening systems for diseases such as diabetic retinopathy (DR), age-related macular degeneration (ARMD), and glaucoma. This paper proposes simple statistical techniques for the detection of the optic disc and macula for calculating the diameter of the optic disc and the distance between the optic disc and macula. The results can be used in automatic diagnosis or monitoring systems developed for retinal diseases. A tool is provided for verifying the location of the optic disc and macula to increase reliability. This study also uses the weighted-distance method to extend the healthy parts of a retinal image. About four hundred retinal fundus images of different qualities are used for testing the system. A detection rate of 97% of the optic disc and macula, an accuracy of 95% of the diameter of the optic disc, and an accuracy of 97% of the positions of the optic disc and macula are obtained.