A computer-readable medium for providing navigational directions to a user to locate a target anatomical object during a medical procedure via a medical imaging system , comprising instructions which, when executed by a computer, cause the computer to carry out the following steps: selecting an anatomical region surrounding the target anatomical object ; generating a plurality of real-time two-dimensional images of scenes from the anatomical region surrounding the target anatomical object and providing the plurality of real-time two-dimensional images to a controller ; and characterised by comprising: developing and training a deep learning network to automatically detect and identify the scenes from the anatomical region surrounding the target anatomical object , wherein the deep learning network comprises a deep convolutional neural network or a recurrent neural network; automatically mapping each of the plurality of real-time two-dimensional images from the anatomical region surrounding the target anatomical object based on a relative spatial location and a relative temporal location of each of the identified scenes in the anatomical region via the deep learning network; and providing directions to the user to locate the target anatomical object during the medical procedure based on the relative spatial location and the relative temporal location of each of the identified scenes . selecting an anatomical region surrounding the target anatomical object ; generating a plurality of real-time two-dimensional images of scenes from the anatomical region surrounding the target anatomical object and providing the plurality of real-time two-dimensional images to a controller ; and characterised by comprising: developing and training a deep learning network to automatically detect and identify the scenes from the anatomical region surrounding the target anatomical object , wherein the deep learning network comprises a deep convolutional neural network or a recurrent neural network; automatically mapping each of the plurality of real-time two-dimensional images from the anatomical region surrounding the target anatomical object based on a relative spatial location and a relative temporal location of each of the identified scenes in the anatomical region via the deep learning network; and providing directions to the user to locate the target anatomical object during the medical procedure based on the relative spatial location and the relative temporal location of each of the identified scenes . developing and training a deep learning network to automatically detect and identify the scenes from the anatomical region surrounding the target anatomical object , wherein the deep learning network comprises a deep convolutional neural network or a recurrent neural network; automatically mapping each of the plurality of real-time two-dimensional images from the anatomical region surrounding the target anatomical object based on a relative spatial location and a relative temporal location of each of the identified scenes in the anatomical region via the deep learning network; and providing directions to the user to locate the target anatomical object during the medical procedure based on the relative spatial location and the relative temporal location of each of the identified scenes . <EOS>