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: Various aspects of a system and method to process an image for generation of a three-dimensional (3D) view of an anatomical portion are disclosed herein. The system includes an image-processing device configured to receive a plurality of two-dimensional (2D) images associated of an anatomical portion, each with a first field-of-view (FOV) value. A first 3D view of the anatomical portion with a second FOV value, is generated from a 3D reconstruction of the anatomical portion. The 3D reconstruction is obtained by use of a set of 2D image frames selected from the received plurality of 2D images. The second FOV value is greater than the first FOV value of each of the plurality of 2D images of the anatomical portion. A second 3D view is generated, based on the alignment of the generated first 3D view with 3D data associated with a pre-operative state of the anatomical portion.

Abstract: A 3D multiview reconstruction method takes a sequence of 2D stereo images from a narrow field-of-view imager (e.g., camera) and reconstructs a 3D representation of the wide field-of-view object or scene. The 3D multiview reconstruction method tracks 2D image pixels across neighboring frames and constraints for frame integration via 3D model construction.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: Various aspects of a system and a method to provide assistance in a surgery in presence of tissue deformation are disclosed herein. In accordance with an embodiment, the system includes an electronic device that receives one or more tissue material properties of a plurality of surface structures of an anatomical portion. One or more boundary conditions associated with the anatomical portion may also be received. Surface displacement of the anatomical portion may be determined by matching a first surface of the anatomical portion before deformation with a corresponding second surface of the anatomical portion after the deformation. The volume displacement field of the anatomical portion may be computed based on the determined surface displacement, the received one or more tissue material properties, and the received one or more boundary conditions.

Abstract: Various aspects of a system and a method to process multimodal images are disclosed herein. In accordance with an embodiment, the system includes an image-processing device that generates a structured point cloud, which represents edge points of an anatomical portion. The structured point cloud is generated based on shrink-wrapping of an unstructured point cloud to a boundary of the anatomical portion. Diffusion filtering is performed to dilate edge points that correspond to the structured point cloud to mutually connect the edge points on the structured point cloud. A mask is created for the anatomical portion based on the diffusion filtering.

Abstract: Various aspects of a method and a system for segmentation of vascular structure in a volumetric image dataset are disclosed herein. The method comprises initial segmentation of an input volumetric image dataset to obtain a main vessel structure and a plurality of broken segments. A weighted path is computed between the main vessel structure and a broken segment of the plurality of broken segments. The computation of the weighted path is based on at least one or more parameters associated with a first voxel of the broken segment and a second voxel of the main vessel structure. A valid, weighted path is determined between the main vessel structure and a broken segment of the plurality of broken segments, based on the computed weighted path and one or more pre-specified conditions. Based on the determined valid, weighted path, an output volumetric image dataset is generated by performance of a final segmentation on a gradient field.

Abstract: Various aspects of a system and method for utilization of multiple-camera network to capture static and/or motion scenes are disclosed herein. The system comprises a plurality of unmanned aerial vehicles (UAVs). Each of the plurality of UAVs is associated with an imaging device configured to capture a plurality of images. A first UAV of the plurality of UAVs comprises a first imaging device configured to capture a first set of images of one or more static and/or moving objects. The first UAV is configured to receive focal lens information, current location and current orientation from one or more imaging devices. A target location and a target orientation of each of the one or more imaging devices are determined. Control information is communicated to the one or more other UAVs to modify the current location and current orientation to the determined target location and orientation of each of the one or more imaging devices.

Abstract: An apparatus and method for performing automatic 3D image segmentation and reconstruction of organ structures, which is particularly well-suited for use on cortical surfaces is presented. A brain extraction process removes non-brain image elements, then classifies brain tissue as to type in preparation for a cerebrum segmentation process that determines which portions of the image information belong to specific physiological structures. Ventricle filling is performed on the image data based on information from a ventricle extraction process. A reconstruction process follows in which specific surfaces, such as white matter (WM) and grey matter (GM), are reconstructed.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: Certain aspects of an apparatus and method for automatic ER/PR scoring of tissue samples may include for determining a cancer diagnosis score comprising identifying a positive stained nucleus in a slide image of the tissue sample, identifying a negative stained nucleus in the slide image, computing a proportion score based on number of the positive stained nucleus identified and number of the negative stained nucleus identified and determining the cancer diagnosis score based on the proportion.

Abstract: A blood detection system, and a method of operation thereof, including: a camera for obtaining an input image frame; and a processing unit connected to the camera, the processing unit including: an image block module for extracting image blocks from the input image frame, and an automatic blood detection module, coupled to the image block module, for calculating an overall blood probability of the image blocks including: determining a red color dominance probability, determining a red color deviation probability, and determining a red color colorfulness probability.

Abstract: An apparatus and method for performing automatic 3D image segmentation and reconstruction of organ structures, which is particularly well-suited for use on cortical surfaces is presented. A brain extraction process removes non-brain image elements, then classifies brain tissue as to type in preparation for a cerebrum segmentation process that determines which portions of the image information belong to specific physiological structures. Ventricle filling is performed on the image data based on information from a ventricle extraction process. A reconstruction process follows in which specific surfaces, such as white matter (WM) and grey matter (GM), are reconstructed.

Abstract: Convolution neural networks are able to be trained using a GPU and a CPU. To efficiently utilize a device's resources, the HetNet and HybNet approaches have been developed. The HetNet approach separates batches into partitions such that the GPU and CPU process separate batches. The HybNet approach separates the layers of a convolution neural network for the GPU and CPU.

Abstract: An apparatus and method for performing automatic 3D image segmentation and reconstruction of organ structures, which is particularly well-suited for use on cortical surfaces is presented. A brain extraction process removes non-brain image elements, then classifies brain tissue as to type in preparation for a cerebrum segmentation process that determines which portions of the image information belong to specific physiological structures. Ventricle filling is performed on the image data based on information from a ventricle extraction process. A reconstruction process follows in which specific surfaces, such as white matter (WM) and grey matter (GM), are reconstructed.

Abstract: An apparatus and method for performing automatic 3D image segmentation and reconstruction of organ structures, which is particularly well-suited for use on cortical surfaces is presented. A brain extraction process removes non-brain image elements, then classifies brain tissue as to type in preparation for a cerebrum segmentation process that determines which portions of the image information belong to specific physiological structures. Ventricle filling is performed on the image data based on information from a ventricle extraction process. A reconstruction process follows in which specific surfaces, such as white matter (WM) and grey matter (GM), are reconstructed.

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.

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: 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.