Abstract: Embodiments described herein provide for training a machine learning model for automatic organ segmentation. A processor executes a machine learning model using an image to output at least one predicted organ label for a plurality of pixels of the image. Upon transmitting the at least one predicted organ label to a correction computing device, the processor receives one or more image fragments identifying corrections to the at least one predicted organ label. Upon transmitting the one or more image fragments and the image to a plurality of reviewer computing devices, the processor receives a plurality of inputs indicating whether the one or more image fragments are correct. When a number of inputs indicating an image fragment of the image fragments is correct exceeds a threshold, the processor aggregates the image fragment into a training data set. The processor trains the machine learning model with the training data set.

Abstract: Deep learning approaches automatically segment at least some breast tissue images while non-deep learning approaches automatically segment organs-at-risk. Both three-dimensional CT imaging information and two-dimensional orthogonal topogram imaging information can be used to determine virtual-skin volume. The foregoing imaging information can also serve to automatically determine a body outline for at least a portion of the patient. That body outline, along with the virtual-skin volume and registration information can serve as inputs to automatically calculate radiation treatment platform trajectories, collision detection information, and virtual dry run information of treatment delivery per the optimized radiation treatment plan.

Abstract: Deep learning approaches automatically segment at least some breast tissue images while non-deep learning approaches automatically segment organs-at-risk. Both three-dimensional CT imaging information and two-dimensional orthogonal topogram imaging information can be used to determine virtual-skin volume. The foregoing imaging information can also serve to automatically determine a body outline for at least a portion of the patient. That body outline, along with the virtual-skin volume and registration information can serve as inputs to automatically calculate radiation treatment platform trajectories, collision detection information, and virtual dry run information of treatment delivery per the optimized radiation treatment plan.

Abstract: An apparatus for use in a medical process that involves a particle accelerator, includes: a processing unit configured to obtain treatment plan information, obtain a viewing direction of a user of the apparatus, and process the treatment plan information based on the viewing direction of the user of the apparatus to create a graphical representation of the treatment plan information for presentation to the user of the apparatus; and a screen for displaying the graphical representation.

Abstract: An apparatus for use in a medical process that involves a particle accelerator, includes: a processing unit configured to obtain medical information, obtain a viewing direction of a user of the apparatus, and process the medical information based on the viewing direction of the user of the apparatus to create a graphical representation of the medical information for presentation to the user of the apparatus; and a screen for displaying the graphical representation.

Abstract: An apparatus for use in a medical process that involves a particle accelerator, includes: a processing unit configured to obtain medical information, obtain a viewing direction of a user of the apparatus, and process the medical information based on the viewing direction of the user of the apparatus to create a graphical representation of the medical information for presentation to the user of the apparatus; and a screen for displaying the graphical representation.

Abstract: An apparatus for use in a medical process that involves a particle accelerator, includes: a processing unit configured to obtain treatment plan information, obtain a viewing direction of a user of the apparatus, and process the treatment plan information based on the viewing direction of the user of the apparatus to create a graphical representation of the treatment plan information for presentation to the user of the apparatus; and a screen for displaying the graphical representation.

Abstract: An apparatus for use in a medical process, includes: a haptic device configured to provide mechanical feedback to a user; and a processing unit communicatively coupled to the haptic device, wherein the processing unit is configured to obtain tissue information, and provide a signal to operate the haptic device based on the tissue information for assisting the user in performing treatment planning. An apparatus for use in a medical process, includes: a feedback device configured to provide visual feedback to a user; and a processing unit communicatively coupled to the feedback device; wherein the visual feedback comprises a displayed object, wherein a position of the displayed object is variable in response to operation of a user control, and wherein the processing unit is configured to obtain tissue information, and to change a behavior of the user control based on the tissue information.