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Image feature classification and localization using discriminative representations for robotic surgical control

机译:图像特征分类和定位使用判别表示进行机器人手术控制

摘要

A method for digital image classification and localization includes receiving a digital image of a biological organism from an imaging apparatus, the digital image comprising a plurality of intensities on a 2-dimensional grid of points, generating a plurality of discriminative representations of the 2D digital image by extracting dominant characteristics of the image from three different viewpoints, where the plurality of discriminative representations form a 3-dimensional digital image, combining the 3D digital image with the 2D digital image in a convolutional neural network that outputs a 3-channel feature map that localizes image abnormalities in each of the three channels and includes a detection confidence that each abnormalities is a neoplasm, providing the 3-channel feature map to a controller of a robotic surgical device where the robotic surgical device uses the 3-channel feature map to locate the neoplasm within the biological organism in a surgical procedure for treating the neoplasm.
机译:一种用于数字图像分类和定位的方法,包括从成像设备接收生物体的数字图像,该数字图像包括在二维点网格上的多个强度,生成该2D数字图像的多个判别表示。通过从三个不同的角度提取图像的主要特征,其中多个判别表示形成一个3维数字图像,并在一个卷积神经网络中将3D数字图像和2D数字图像组合在一起,并输出一个3通道特征图,在三个通道中的每个通道中定位图像异常,并包括每个异常都是肿瘤的检测置信度,将3通道特征图提供给机器人手术设备的控制器,其中机器人手术设备使用3通道特征图进行定位外科手术中生物体内的肿瘤肿瘤。

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