Abstract: The present invention relates to deep learning for automated segmentation of a medical image. More particularly, the present invention relates to deep learning for automated segmentation of anatomical regions and lesions in mammography screening and clinical assessment. According to a first aspect, there is provided a computer-aided method of segmenting regions in medical images, the method comprising the steps of: receiving input data; analysing the input data by identifying one or more regions; determining one or more characteristics for the one or more regions in the input data; and generating output segmentation data in dependence upon the characteristics for the one or more regions.

Abstract: The present invention relates to the identification of regions of interest in medical images. More particularly, the present invention relates to the identification of regions of interest in medical images based on encoding and/or classification methods trained on multiple types of medical imaging data. Aspects and/or embodiments seek to provide a method for training an encoder and/or classifier based on multimodal data inputs in order to classify regions of interest in medical images based on a single modality of data input source.