At present, computed tomography (CT) images of interest for medical diagnosis are manually selected among a series of images by physicians. This study uses image processing to automatically select the regions of the nasal vestibule and nasal septum using a back-propagation neural network. Three-dimensional (3D) image reconstructions of the nasal regions are conducted to obtain the 3D spatial information. 3D images of the nasal cavity, nasopharynx, and paranasal sinuses are also reconstructed. The representative points are labeled in three surgically risky locations, namely the anterior cranial fossa of the brain and the inferior and medial edges of the orbital rim. The nasal and paranasal sinus conformation and marked points are presented to assist surgeons in the preoperative evaluation. The overall recognition rate of the system for the nasal vestibule and nasal septum is 99.7%. The 3D images are considered to be beneficial by an otolaryngologist from Tri-Service General Hospital in Taiwan. The proposed method can facilitate the preoperative evaluation and improve the quality of medical care.