Abstract: Systems and methods for detecting and classifying clinical features in medical images are disclosed. Natural language processes are applied to speech received from a dictation system to determine clinical and anatomical information for a medical image being viewed. In some examples, gaze location information identifying an eye position is received, as well as an image position for the medical image being viewed. Features of the medical image are detected and classified based on machine learning models. Anatomical associations are generated based on one or more of the classifications, the anatomical information, the gaze information, and the image position. The machine learning models can be trained based on the anatomical associations. In some examples, reports are generated based on the anatomical associations.

Abstract: Systems and methods for detecting and classifying clinical features in medical images are disclosed. Natural language processes are applied to speech received from a dictation system to determine clinical and anatomical information for a medical image being viewed. In some examples, gaze location information identifying an eye position is received, as well as an image position for the medical image being viewed. Features of the medical image are detected and classified based on machine learning models. Anatomical associations are generated based on one or more of the classifications, the anatomical information, the gaze information, and the image position. The machine learning models can be trained based on the anatomical associations. In some examples, reports are generated based on the anatomical associations.

Abstract: Facilitating viewer comparison of a plurality of medical images of at least one body part on a softcopy review workstation is described. First and second medical images are displayed such that the second medical image appears as a spatially registered underlay to the first medical image exposed through an aperture therein. The aperture comprises at least one edge that is viewer-manipulable in a back-and-forth manner so that the first and second medical images can be visually compared with minimal eye movement. For a temporal comparison embodiment, the first and second medical images comprise identical views of the same body part acquired at different times. For a cross-modality comparison embodiment, the first and second medical images are acquired substantially concurrently, or at different times, using different medical imaging modalities. For a bilateral comparison embodiment, the first and second images are corresponding views of two laterally corresponding body parts.

Abstract: Facilitating viewer comparison of a plurality of medical images of at least one body part on a softcopy review workstation is described. First and second medical images are displayed such that the second medical image appears as a spatially registered underlay to the first medical image exposed through an aperture therein. The aperture comprises at least one edge that is viewer-manipulable in a back-and-forth manner so that the first and second medical images can be visually compared with minimal eye movement. For a temporal comparison embodiment, the first and second medical images comprise identical views of the same body part acquired at different times. For a cross-modality comparison embodiment, the first and second medical images are acquired substantially concurrently, or at different times, using different medical imaging modalities. For a bilateral comparison embodiment, the first and second images are corresponding views of two laterally corresponding body parts.