1. A method for automated machine analysis of medical imaging, comprising: using a computing system comprising at least one electronic processor circuit to access from a data storage device, or cloud-based storage, complementary image data of a biological tissue structure (BTS) obtained by using a medical image acquisition system, the complementary image data comprising a plurality of two-dimensional images, obtained from a three-dimensional or two-dimensional dataset, which represent different views of the BTS respectively aligned with a plurality of distinct image planes; process each of the plurality of two-dimensional images respectively using one of a plurality of separate convolutional neural networks (CNNs) instantiated by the computing system; determine as a result of the processing performed by each CNN a probability map for one of the plurality of two-dimensional images which specifies for each pixel contained therein a probability that the pixel belongs to one of a plurality of pre-defined object classes; and adaptively fuse the probability maps produced in each of the plurality of separate CNNs to produce a segmented output representative of the BTS.