Abstract: According to an aspect, a method includes receiving, by a client application, a video stream of a live broadcast from a messaging platform, displaying, by the client application, the video stream of the live broadcast on a user interface of the client application, receiving, via a timestamp selector on the user interface, a selection of a time location in a time window of a timeline of the video stream of the live broadcast, generating, by the client application, a timestamp based on the time location received via the timestamp selector, and sending, by the client application, a message that includes the timestamp to the messaging platform to share the video stream of the live broadcast on the messaging platform such that playback of the shared video stream of the live broadcast is configured to start at the time location indicated by the timestamp.

Abstract: According to an aspect, a method includes receiving, by a client application, a video stream of a live broadcast from a messaging platform, displaying, by the client application, the video stream of the live broadcast on a user interface of the client application, receiving, via a timestamp selector on the user interface, a selection of a time location in a time window of a timeline of the video stream of the live broadcast, generating, by the client application, a timestamp based on the time location received via the timestamp selector, and sending, by the client application, a message that includes the timestamp to the messaging platform to share the video stream of the live broadcast on the messaging platform such that playback of the shared video stream of the live broadcast is configured to start at the time location indicated by the timestamp.

Abstract: System for performing fully automatic brain tumor and tumor-aware cortex reconstructions upon receiving multi-modal MRI data (T1, T1c, T2, T2-Flair). The system outputs imaging which delineates distinctions between tumors (including tumor edema, and tumor active core), from white matter and gray matter surfaces. In cases where existing MRI model data is insufficient then the model is trained on-the-fly for tumor segmentation and classification. A tumor-aware cortex segmentation that is adaptive to the presence of the tumor is performed using labels, from which the system reconstructs and visualizes both tumor and cortical surfaces for diagnostic and surgical guidance. The technology has been validated using a publicly-available challenge dataset.

Abstract: According to an aspect, a method includes receiving, by a client application, a video stream of a live broadcast from a messaging platform, displaying, by the client application, the video stream of the live broadcast on a user interface of the client application, receiving, via a timestamp selector on the user interface, a selection of a time location in a time window of a timeline of the video stream of the live broadcast, generating, by the client application, a timestamp based on the time location received via the timestamp selector, and sending, by the client application, a message that includes the timestamp to the messaging platform to share the video stream of the live broadcast on the messaging platform such that playback of the shared video stream of the live broadcast is configured to start at the time location indicated by the timestamp.

Abstract: An inter-patient brain registration method for data normalization deformably aligns two brain images obtained from different patients even with tumor presence.

Abstract: Various aspects of a method and system to localize surgical tools during anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in an image-processing engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes determination of one or more physical characteristics of one or more surgical tools present in the one or more video frames, based on one or more color and geometric constraints. Thereafter, two-dimensional (2D) masks of the one or more surgical tools are detected, based on the one or more physical characteristics of the one or more surgical tools. Further, poses of the one or more surgical tools are estimated, when the 2D masks of the one or more surgical tools are occluded at tips and/or ends of the one or more surgical tools.

Abstract: A fully automatic brain tumor segmentation and classification method and system improve the healthcare experience with machine intelligence. The automatic brain tumor segmentation and classification method and system utilize whole tumor segmentation and multi-class tumor segmentation to provide accurate analysis.

Abstract: An inter-patient brain registration method for data normalization deformably aligns two brain images obtained from different patients even with tumor presence.

Abstract: Various aspects of a method and system to localize surgical tools during anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in an image-processing engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes determination of one or more physical characteristics of one or more surgical tools present in the one or more video frames, based on one or more color and geometric constraints. Thereafter, two-dimensional (2D) masks of the one or more surgical tools are detected, based on the one or more physical characteristics of the one or more surgical tools. Further, poses of the one or more surgical tools are estimated, when the 2D masks of the one or more surgical tools are occluded at tips and/or ends of the one or more surgical tools.

Abstract: A fully automatic brain tumor segmentation and classification method and system improve the healthcare experience with machine intelligence. The automatic brain tumor segmentation and classification method and system utilize whole tumor segmentation and multi-class tumor segmentation to provide accurate analysis.

Abstract: Various aspects of a method and system to localize surgical tools during anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in an image-processing engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes determination of one or more physical characteristics of one or more surgical tools present in the one or more video frames, based on one or more color and geometric constraints. Thereafter, two-dimensional (2D) masks of the one or more surgical tools are detected, based on the one or more physical characteristics of the one or more surgical tools. Further, poses of the one or more surgical tools are estimated, when the 2D masks of the one or more surgical tools are occluded at tips and/or ends of the one or more surgical tools.

Abstract: A fully automatic brain tumor segmentation and classification method and system improve the healthcare experience with machine intelligence. The automatic brain tumor segmentation and classification method and system utilize whole tumor segmentation and multi-class tumor segmentation to provide accurate analysis.

Abstract: A fully automatic brain tumor segmentation and classification method and system improve the healthcare experience with machine intelligence. The automatic brain tumor segmentation and classification method and system utilize whole tumor segmentation and multi-class tumor segmentation to provide accurate analysis.

Abstract: System for performing fully automatic brain tumor and tumor-aware cortex reconstructions upon receiving multi-modal MRI data (T1, T1c, T2, T2-Flair). The system outputs imaging which delineates distinctions between tumors (including tumor edema, and tumor active core), from white matter and gray matter surfaces. In cases where existing MRI model data is insufficient then the model is trained on-the-fly for tumor segmentation and classification. A tumor-aware cortex segmentation that is adaptive to the presence of the tumor is performed using labels, from which the system reconstructs and visualizes both tumor and cortical surfaces for diagnostic and surgical guidance. The technology has been validated using a publicly-available challenge dataset.

Abstract: Various aspects of a system and method for smoke detection during an anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in a surgical scene analysis engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes the estimation of a partially visible region in a current video frame, based on a temporal difference between the current video frame and a previous video frame from the one or more video frames. Thereafter, one or more candidate pixels are detected in the estimated partially visible region in the current video frame. Further, a smoke region is determined in the partially visible region, based on pruning of one or more candidate pixels.

Abstract: Various aspects of a method and system for detection of surgical gauze during anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in an image-processing engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes the determination of a set of pixel characteristics based on color filtering of at least a portion of a video frame. Thereafter, one or more blocks of pixels of a portion of a surgical gauze are detected in the video frame based on the set of pixel characteristics. Further, additional pixels that correspond to a remaining portion of the surgical gauze are identified based on a plurality of metrics. The surgical gauze is recognized in the video frame based on the detection of the one or more blocks of pixels and the identification of the additional pixels.

Abstract: A method for reconstructing a three-dimension image includes receiving a plurality of two-dimensional images and projection information of the two-dimensional images, projecting a plurality of rays onto the plurality of two-dimensional images, determining correspondence information between pixels of different ones of the plurality of two-dimensional images, determining a value of each of the pixels, and reconstructing a three-dimension image by integrating the plurality of rays, wherein a position on each ray can be associated to one pixel of the plurality of two-dimensional images.

Abstract: Methods, systems, and computer readable media for real-time 2D/3D deformable registration using metric learning are disclosed. According to one aspect, a method for real-time 2D/3D deformable registration using metric learning includes creating a catalog of simulated 2D projection images based on a reference 3D image and a shape space of 3D deformations, where each entry in the catalog is created by: applying to the reference 3D image a set of deformation parameters from the shape space of deformations; simulating a 2D projection of the result; associating the simulated 2D projection image with the deformation parameters used to create the simulated 2D projection image; and storing the simulated 2D projection image and associated deformation parameters in the catalog.

Abstract: Various aspects of a method and system for content management of video images of anatomical regions are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in a content processing device, which is communicatively coupled to an image-capturing device. The method includes identification of one or more non-tissue regions in a video image of an anatomical region. The video image is generated by the image-capturing device. Thereafter, one or more content identifiers are determined for the identified one or more non-tissue regions. Further, each of the determined one or more content identifiers are associated with a corresponding non-tissue region that corresponds to the identified one or more non-tissue regions.

Abstract: Various aspects of a method and system for detection of surgical gauze during anatomical surgery are disclosed herein. In accordance with an embodiment of the disclosure, the method is implementable in an image-processing engine, which is communicatively coupled to an image-capturing device that captures one or more video frames. The method includes the determination of a set of pixel characteristics based on color filtering of at least a portion of a video frame. Thereafter, one or more blocks of pixels of a portion of a surgical gauze are detected in the video frame based on the set of pixel characteristics. Further, additional pixels that correspond to a remaining portion of the surgical gauze are identified based on a plurality of metrics. The surgical gauze is recognized in the video frame based on the detection of the one or more blocks of pixels and the identification of the additional pixels.