Abstract: A training platform, a method and a computer-readable medium for evaluating users in capturing images of an internal anatomical region for the analysis of organs. Automated machine learning models, trained on a dataset of labelled training images associated with different imaging device positions, are used. The one or more automated machine learning models are used to process an image resulting from a user positioning an imaging device at various imaging device positions relative to a training manikin, a human or an animal, to determine whether the generated image corresponds to a predefined view required for the analysis of the organ features shown therein. An output indicative of whether the generated image corresponds to the predefined view expected for organ analysis and measurements is provided.

Abstract: A training platform, a method and a computer-readable medium for evaluating users in capturing images of an internal anatomical region for the analysis of organs. Automated machine learning models, trained on a dataset of labelled training images associated with different imaging device positions, are used. The one or more automated machine learning models are used to process an image resulting from a user positioning an imaging device at various imaging device positions relative to a training manikin, a human or an animal, to determine whether the generated image corresponds to a predefined view required for the analysis of the organ features shown therein. An output indicative of whether the generated image corresponds to the predefined view expected for organ analysis and measurements is provided.