Abstract: A computer system generates a clinical summary for a patient based on machine learning. One or more templates are generated, each indicating medical information for a corresponding clinical summary with respect to a medical condition of a patient. Preferences for medical information for each corresponding clinical summary are learned based on a history of desired medical information for clinical summaries for the medical condition. The learned preferences are applied to the one or more templates. A clinical summary is generated with respect to the medical condition of the patient based on the one or more templates with the learned preferences. Embodiments of the present invention further include a method and program product for generating a clinical summary for a patient based on machine learning in substantially the same manner described above.

Abstract: Methods, systems, and computer readable media are provided for processing medical images. One or more prior medical images are aligned with a current medical image. Image subtraction between the current medical image and the one or more prior medical images is performed to produce one or more difference images. The one or more difference images are applied to a machine learning model to determine a presence or an absence of a medical condition.

Abstract: A computer system generates a clinical summary for a patient based on machine learning. One or more templates are generated, each indicating medical information for a corresponding clinical summary with respect to a medical condition of a patient. Preferences for medical information for each corresponding clinical summary are learned based on a history of desired medical information for clinical summaries for the medical condition. The learned preferences are applied to the one or more templates. A clinical summary is generated with respect to the medical condition of the patient based on the one or more templates with the learned preferences. Embodiments of the present invention further include a method and program product for generating a clinical summary for a patient based on machine learning in substantially the same manner described above.

Abstract: Methods, systems, and computer readable media are provided for processing medical images. One or more prior medical images are aligned with a current medical image. Image subtraction between the current medical image and the one or more prior medical images is performed to produce one or more difference images. The one or more difference images are applied to a machine learning model to determine a presence or an absence of a medical condition.

Abstract: An image management system (10), includes a PACS system. The PACS system (10) includes a PACS server (20) coupled to a communications network (22) and a plurality of PACS workstations (40) also coupled to a communications network (22). Each PACS workstation (40) is configured to receive two dimensional image information and produce a three dimensional image rendering on the PACS workstation (40). The three dimensional image rendering is communicated to the PACS server (20) for storage and later retrieval.

Abstract: The present invention, in one form, is a system for simultaneously displaying an image object generated from an imaging system and a graphical object so that each object is fully visible. More specifically, after generating the image object, a graphical object is generated having a partial opacity value. The image object and graphical object are then sorted and combined so that the graphical object is in front of, or overlays, the image object without blocking or obscuring the information included in the image object. Particularly, a final image is generated by combining a destination value for components of each object.

Abstract: An image management system (10), such as a PACS system is disclosed. The PACS system includes a PACS server (20) coupled to a communications network (22) and a plurality of PACS workstations (40) also coupled to a communications network (22). Each PACS workstation (40) is configured to receive two dimensional image information and provide incremental volume rendering on the PACS workstation (40) while the two dimensional image information is being received.

Abstract: A workstation includes a regression testing program which tests application programs developed on the workstation using stored test scripts. A test directory tree is maintained to mirror a source code directory tree, and the test directory tree is employed to select the test scripts to be used in testing any newly compiled application programs.

Abstract: A universal interface apparatus for use with any of several different imaging systems for facilitating a plurality of different imaging modalities, the interface including at least function icons in a function navigation space and a workspace, each of the function icons corresponding to a process which is common among all of the imaging modalities, the interface Also accessing data tables corresponding to specific workflow protocols for medical facility radiologists and/or for a medical facility in general, the tables identifying function icons and other icons for guiding a technologist through a properly orchestrated imaging process.

Abstract: A universal interface apparatus for use with any of several different imaging systems for facilitating a plurality of different imaging modalities, the interface including at least function icons in a function navigation space and a workspace, each of the function icons corresponding to a process which is common among all of the imaging modalities, the interface also accessing data tables corresponding to specific workflow protocols for medical facility radiologists and/or for a medical facility in general, the tables identifying function icons and other icons for guiding a technologist through a properly orchestrated imaging process.

Abstract: A graphic workstation receives digitized medical images and the user creates textual information that is to be displayed on the images. Instead of overlaying the text, the text data is blended with the image data such that the text appears semi-transparent and when displayed the underlying image data may be seen. The medical image may be fully restored from the blended image by a calculation based upon the blended image, the text data and alpha.

Abstract: A graphic workstation receives digitized medical images and the user creates textual information that is to be displayed on the images. The text along with associated properties are packaged as a data structure along with a set of properties, and the data structure is passed through a pipeline having a series of formatters. The formatters are easily configured by the user to modify the properties of the text data structures as they flow through the pipeline prior to being rendered on a display.