Advances in medical imaging modalities have made it possible to acquire volume images. One of the key steps used to split the raw volume image into meaningful sub-volumes is three-dimensional (3D) edge detection. This paper describes a new approach for 3D edge detection. It is based on the two-dimensional (2D) hybrid edge detector, which consists of a combination of the first and second order differential edge detectors. It was shown in the 2D case that the combination of the two differential edge detectors gave accurate edge localization whilst maintaining immunity to the noise in the image. Results using the 3D hybrid edge detector based on synthetic and real images are presented. They are also compared to the results using the 3D Gradient of the Gaussian (GoG) detector and the 3D Laplacian of the Gaussian (LoG) detector.