Abstract: Automated peer review of medical imagery is provided. In some embodiments, at least one finding is determined for a present study. The present study has a subject anatomy. Based on the at least one finding and the subject anatomy, at least one prior study is selected. The at least one prior study has subject anatomy related to the subject anatomy of the present study and does not include the at least one finding. The at least one prior study is provided to a user for review with respect to the at least one finding.

Abstract: Retrospective review of electronic medical records is provided. In some embodiments, a retrospective review of a plurality of electronic medical records is performed. The retrospective review includes searching for electronic medical records relevant to a medical condition. Based on the retrospective review, a plurality of studies most relevant to a present study is determined. Each of the plurality of studies are flagged for supplemental review in a worklist.

Abstract: Measurement of medical images as a hybrid cloud service is provided. In various embodiments, pre-trained parameters are received at a client from a remote server. A local cognitive system is instantiated using the pre-trained parameters. The cognitive system is applied to evaluate a medical image. A result is sent to the remote server for training of a remote cognitive system.

Abstract: User interfaces for navigating medical studies are provided. In various embodiments, a human avatar having a plurality of selectable regions is displayed. Indications of the presence of prior studies are displayed corresponding to the plurality of selectable regions. A selection of a region of the plurality of selectable regions is received from a user. An indication of one or more prior study is displayed corresponding to the selected region.

Abstract: Hybrid rendering systems for medical imaging applications are provided. In some embodiments, an indication of a viewing mode is received at a medical image viewer from a user. The viewing mode is a diagnostic mode or a referential mode. A plurality of characteristics of the medical image viewer are determined. Based upon the viewing mode and the plurality of characteristics of the medical image viewer, a rendering mode is determined. The rendering mode is a server-side rendering mode or a client-side rendering mode. A request for medical imagery is sent. The request conforms to the rendering mode. The medical imagery is rendered according to the rendering mode. The requested medical imagery is displayed on the medical image viewer.

Abstract: Self-describing calibration targets for inclusion in medical imagery and automated quality control and calibration are provided. In various embodiments, a medical image is received. The medical image includes a calibration target in its field of view. A description of the calibration target is read from the calibration target. The description includes size and at least one color reference. Based on the description of the calibration target, correction parameters are determined for the medical image. The correction parameters include pixel shape correction parameters, scale correction parameters, contrast correction parameters, or color correction parameters.

Abstract: Carrying forward a spine label between studies is provided. In some embodiments, a first medical image of a subject's spine is provided. With the first image at least one label identifying a feature of the spine is provided. The first medical image is displayed to a user with the at least one label. At least one change is received from the user to the at least one label, yielding at least one updated label. The at least one updated label is applied to a second medical image. A three dimensional representation of the updated label is displayed.

Abstract: Multiple algorithm lesion segmentation using an atlas is provided. In various embodiments, a plurality of medical images are read from an image repository. Each of the plurality of medical images has a source modality. Each of the plurality of medical images is registered to an anatomical atlas. An anatomical region depicted in each of the plurality of medical images is determined thereby. Based upon the source modality and the anatomical region depicted in each of the plurality of medical images, one of a plurality of segmentation algorithms is selected for each of the plurality of medical images. The selected segmentation algorithms are applied to each of the plurality of medical images. The results of the selected segmentation algorithms are displayed.

Abstract: A system for viewing session takeover is provided. A plurality of user accounts have access to patient medical data images. A locking mechanism is operable by each user to prevent access to patient medical data until subsequent user authentication, without terminating a viewing session. A storage medium maintains configuration parameters associated with the primary user account. A session controller establishes a viewing session by retrieving the patient medical data for viewing on the display. The session controller applies the configuration parameters associated with the primary user account to the viewing session of the secondary user. A log records each user access associated with each viewing session.

Abstract: Multi-step vessel segmentation and analysis is provided. In various embodiments, a branch detection algorithm is applied to a medical image to determine a plurality of branches of a blood vessel appearing in the medical image. A plurality of segments of the blood vessel appearing in the medical image is determined. Each of the plurality of segments is bounded by one of the plurality of branches. An edge detection algorithm is applied piecewise to each of the plurality of segments. A composite blood vessel outline is formed from the piecewise edge detection.

Abstract: Hybrid rendering systems for medical imaging applications are provided. In some embodiments, an indication of a viewing mode is received at a medical image viewer from a user. The viewing mode is a diagnostic mode or a referential mode. A plurality of characteristics of the medical image viewer are determined. Based upon the viewing mode and the plurality of characteristics of the medical image viewer, a rendering mode is determined. The rendering mode is a server-side rendering mode or a client-side rendering mode. A request for medical imagery is sent. The request conforms to the rendering mode. The medical imagery is rendered according to the rendering mode. The requested medical imagery is displayed on the medical image viewer.

Abstract: A system for viewing session takeover is provided. A plurality of user accounts have access to patient medical data images. A locking mechanism is operable by each user to prevent access to patient medical data until subsequent user authentication, without terminating a viewing session. A storage medium maintains configuration parameters associated with the primary user account. A session controller establishes a viewing session by retrieving the patient medical data for viewing on the display. The session controller applies the configuration parameters associated with the primary user account to the viewing session of the secondary user. A log records each user access associated with each viewing session.

Abstract: Measurement of medical images as a hybrid cloud service is provided. In various embodiments, pre-trained parameters are received at a client from a remote server. A local cognitive system is instantiated using the pre-trained parameters. The cognitive system is applied to evaluate a medical image. A result is sent to the remote server for training of a remote cognitive system.

Abstract: Carrying forward a spine label between studies is provided. In some embodiments, a first medical image of a subject's spine is provided. With the first image at least one label identifying a feature of the spine is provided. The first medical image is displayed to a user with the at least one label. At least one change is received from the user to the at least one label, yielding at least one updated label. The at least one updated label is applied to a second medical image. A three dimensional representation of the updated label is displayed.

Abstract: Automated peer review of medical imagery is provided. In some embodiments, at least one finding is determined for a present study. The present study has a subject anatomy. Based on the at least one finding and the subject anatomy, at least one prior study is selected. The at least one prior study has subject anatomy related to the subject anatomy of the present study and does not include the at least one finding. The at least one prior study is provided to a user for review with respect to the at least one finding.

Abstract: Retrospective review of electronic medical records is provided. In some embodiments, a retrospective review of a plurality of electronic medical records is performed. The retrospective review includes searching for electronic medical records relevant to a medical condition. Based on the retrospective review, a plurality of studies most relevant to a present study is determined. Each of the plurality of studies are flagged for supplemental review in a worklist.

Abstract: Automatic processing of medical imagery to remove personal health information is provided. In some various embodiments, a structured file containing a medical image and metadata is read. Identifying information of a device that captured the medical image is determined from the structured file. Based on the identifying information, locations within the medical image likely to include personal health information are determined. The locations within the medical image likely to include personal health information are obscured.

Abstract: Multiple algorithm lesion segmentation using an atlas is provided. In various embodiments, a plurality of medical images are read from an image repository. Each of the plurality of medical images has a source modality. Each of the plurality of medical images is registered to an anatomical atlas. An anatomical region depicted in each of the plurality of medical images is determined thereby. Based upon the source modality and the anatomical region depicted in each of the plurality of medical images, one of a plurality of segmentation algorithms is selected for each of the plurality of medical images. The selected segmentation algorithms are applied to each of the plurality of medical images. The results of the selected segmentation algorithms are displayed.

Abstract: Tracking and managing follow-up in diverse distributed medical systems is provided. In some embodiments, an electronic medical record system is continuously monitored. One or more recommendation for follow-up is identified within the electronic medical record system. It is determined whether the recommended follow-up or an equivalent to the recommended follow-up was performed. The determination comprises searching a plurality of medical systems. The plurality of medical systems comprises an electronic medical record system, a picture archiving and communication system, or a medical billing system. A user is notified of any missing follow-up.

Abstract: Multi-step vessel segmentation and analysis is provided. In various embodiments, a branch detection algorithm is applied to a medical image to determine a plurality of branches of a blood vessel appearing in the medical image. A plurality of segments of the blood vessel appearing in the medical image is determined. Each of the plurality of segments is bounded by one of the plurality of branches. An edge detection algorithm is applied piecewise to each of the plurality of segments. A composite blood vessel outline is formed from the piecewise edge detection.