Siemens Healthineers Ag

Rishabh Shah

Kaloian Petkov

Christoph Vetter

Sandra Sudarsky

Daphne Yu

Lev Gretskii

A layout of labels for annotating a rendered image is optimized. A rendered image is obtained, and locations of a plurality of regions of interest in the rendered image are determined. Semantic information associated with the plurality of regions of interest is obtained. Based on the semantic information and the locations of the plurality of regions of interest, and, taking into account a visibility of the labels and a further visibility of the regions of interest in the rendered image, the layout of the labels for annotating the plurality of regions of interest in the rendered image is determined.

Dynamic layout optimization of annotation labels in volume rendering

An exposure value is dynamically adapted for consistent interactive rendering of a volumetric medical dataset. A rendering set of a plurality of rendering types with each rendering type adapted for providing an image dataset derived from the volumetric medical dataset is provided. An image dataset according to a first rendering type using a first exposure value is output. An exposure value for each rendering type within the rendering set is determined based on the first exposure value of the first rendering type and on a consistency requirement for changing rendering types of the image dataset output. Upon receiving a user input for modifying the output of the image dataset, a second rendering type with a second exposure value is selected and output.

Technique for dynamically adapting an exposure value in interactive rendering

Systems and methods for determining rendering parameters based on authored snapshots or templates. In one aspect, clinically relevant snapshots of patient medical data are created by experts to support educational or clinical workflows. Alternatively, the snapshots are created by automation processes from AI-based organ and disease segmentations. In another aspect, clinically relevant templates are generated. Rendering parameters are derived from the snapshots or templates, stored, and then applied for either rendering new data or interactive viewing of existing data.

Systems and methods for automated rendering

Distance estimation is optimized in virtual or augmented reality. A distance map of a surgical instrument to a region of interest is determined, at least at the beginning and when a position of the surgical instrument has changed. A render-image is rendered based on a medical 3D image and the position of the surgical instrument, at least at the beginning and when the position of the surgical instrument has changed. At least the region of interest and those parts of the surgical instrument positioned in the volume of the render-image are shown in the render-image. Based on the distance map, at least for a predefined area of the region of interest, visible, acoustic, and/or haptic distance-information is added.

Method and system for optimizing distance estimation

The present embodiment relates to a renderer and an interactive method for image editing of medical 3D anatomical data. The method includes receiving a dataset with volumetric image data, which have been acquired from an image acquisition modality, and providing a signed distance field data structure of the received dataset. Further, editing operations are received from a user interface for editing at least a part of the provided signed distance field data structure. A visualization of the editing operations is calculated and displayed on a display.

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Wentworth Point, Australia

Rishabh Shah