Compared to other traditional imaging exams, computed tomography (CT) is more efficient, where a digital geometry processing is used to generate a 3D image of an internal structure of an object, or patient, from a series of 2D images obtained during various rotations of the CT scan around the scanned object. Also taking in consideration traditional imaging exams such as MRI or ultrasound, for example, the CT technique uses higher radiation doses than these exams, providing high quality images. However, in order to prevent constant exposures to high radiation doses, low-dose computed tomography (LDCT) scans are often recommended. Nevertheless, the images acquired in LDCT scans are degraded by undesirable artifacts, known as noise, which affects negatively the image quality. In this study, a two-stage filter based on morphological operators and Block-Matching 3D (BM3D) is proposed to remove noise in low-dose dental CT images. The quantitative results obtained by our proposed method demonstrated superior performance when compared to several state of the art techniques. Also, our proposed method obtained better visual performance, removing the noise and preserving details more efficiently than the compared filters.