Abstract: Systems and methods for analyzing dental radiographs use deep neural network architectures, model training procedures and data processing method for automated dental charting and condition detection. The systems and methods produce detailed outputs that are comprehensive analyses of dental radiographs attributing detected conditions to particular teeth.

Abstract: A system for automated image analysis includes an imaging device configured to capture input data of a patient, a processor, and a memory coupled to the processor. The memory has instructions stored thereon, which when executed by the processor, cause the system to: capture input data from the imaging device, the input data including a three-dimensional (3D) image of a portion of a patient; receive the input data from the imaging device; generate a first 3D mask based on the input data; generate a second 3D mask based on the first 3D mask; and determine a diagnostic prediction based on the first 3D mask and the second 3D mask. Generating the second 3D mask includes predicting a plurality of two-dimensional (2D) slices based on the first 3D mask, such that each 2D slice of the plurality of 2D slices is an axial cross-section of the first 3D mask.