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: 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 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: 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: 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: Various aspects of an image-processing system and method to reconstruct a three-dimensional (3D) anatomical surface of an anatomical portion are disclosed herein. The system includes an image-processing device configured to receive a plurality of stereo images of the anatomical portion. A first set of key points with a point density greater than a threshold value is identified. A second set of key points is determined based on filtration of one or more outlier key points from the identified first set of key points. A 3D anatomical surface of the anatomical portion is reconstructed based on disparity of one or more matched key points in the determined second set of key points and a smoothing operation performed on the disparity.

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 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: 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 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 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 an image-processing system and method to reconstruct a three-dimensional (3D) anatomical surface of an anatomical portion are disclosed herein. The system includes an image-processing device configured to receive a plurality of stereo images of the anatomical portion. A first set of key points with a point density greater than a threshold value is identified. A second set of key points is determined based on filtration of one or more outlier key points from the identified first set of key points. A 3D anatomical surface of the anatomical portion is reconstructed based on disparity of one or more matched key points in the determined second set of key points and a smoothing operation performed on the disparity.

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: 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 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.