Abstract: A neural network apparatus receives, as input from a user device, digital imaging information and the clinical information for an aneurysm patient and generates, using a neural network trained for aneurysm outcome prediction, the digital imaging information, and the clinical information, an outcome prediction for at least one intrasaccular implant device for implant in an aneurysm sac identified in the digital imaging information and having a highest predicted likelihood of complete occlusion of the aneurysm sac from a set of potential treatment devices. The apparatus is further configured to output, for display on a device, an identification of the at least one intrasaccular implant device and the outcome prediction for each of the at least one intrasaccular implant device.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Web-based annotation of three dimensional medical imagery is provided. In various embodiments, a plurality of two dimensional medical images is read from a data store. The plurality of two dimensional images is a subset of a three dimensional medical imaging study. The plurality of two dimensional medical images is provided to a remote user. Regional annotations for each of the plurality of medical images are received from the remote user. A volumetric description of the three dimensional imaging study is generated by interpolation of the regional annotations. The volumetric description of the three dimensional imaging is provided for rendering and display to the remote user.

Abstract: Web-based annotation of three dimensional medical imagery is provided. In various embodiments, a plurality of two dimensional medical images is read from a data store. The plurality of two dimensional images is a subset of a three dimensional medical imaging study. The plurality of two dimensional medical images is provided to a remote user. Regional annotations for each of the plurality of medical images are received from the remote user. A volumetric description of the three dimensional imaging study is generated by interpolation of the regional annotations. The volumetric description of the three dimensional imaging is provided for rendering and display to the remote user.

Abstract: Automatic generation of user interfaces from annotation templates is provided. In various embodiments, a medical imaging study is retrieved from a data store. At least one characteristic of the medical imaging study is determined. Based on the at least one characteristic, an annotation configuration is selected. Based on the annotation configuration, an annotation user interface is generated for annotation of the medical imaging study. The annotation user interface and the medical imaging study is displayed to a user.

Abstract: Web-based annotation of three dimensional medical imagery is provided. In various embodiments, a plurality of two dimensional medical images is read from a data store. The plurality of two dimensional images is a subset of a three dimensional medical imaging study. The plurality of two dimensional medical images is provided to a remote user. Regional annotations for each of the plurality of medical images are received from the remote user. A volumetric description of the three dimensional imaging study is generated by interpolation of the regional annotations. The volumetric description of the three dimensional imaging is provided for rendering and display to the remote user.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.

Abstract: Web-based annotation of three dimensional medical imagery is provided. In various embodiments, a plurality of two dimensional medical images is read from a data store. The plurality of two dimensional images is a subset of a three dimensional medical imaging study. The plurality of two dimensional medical images is provided to a remote user. Regional annotations for each of the plurality of medical images are received from the remote user. A volumetric description of the three dimensional imaging study is generated by interpolation of the regional annotations. The volumetric description of the three dimensional imaging is provided for rendering and display to the remote user.

Abstract: Automatic generation of user interfaces from annotation templates is provided. In various embodiments, a medical imaging study is retrieved from a data store. At least one characteristic of the medical imaging study is determined. Based on the at least one characteristic, an annotation configuration is selected. Based on the annotation configuration, an annotation user interface is generated for annotation of the medical imaging study. The annotation user interface and the medical imaging study is displayed to a user.

Abstract: Annotation of large image datasets is provided. In various embodiments, a plurality of medical images is received. At least one collection is formed containing a subset of the plurality of medical images. One or more image from the at least one collection is provided to each of a plurality of remote users. An annotation template is provided to each of the plurality of remote users. Annotations for the one or more image are received from each of the plurality of remote users. The annotations and the plurality of medical images are stored together.