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.

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 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: An interactive communication system includes at least one server, at least one base station for connecting to the server via a network, and at least one wearable device. The at least one wearable device includes a first sensor, a second sensor, a microcontroller, and a wireless communication module. The first sensor is configured for sensing a moving state of the at least one wearable device, and generating a corresponding first sensing signal. The second sensor is configured for sensing whether an object is contacting to or is close to the wearable device, and generating a corresponding second sensing signal. The microcontroller is configured for generating a first controlling signal according to the first sensing signal and the second sensing signal. The wireless communication module is configured for sending the first controlling signal to the least one server via the least one base station.