[引用][C] 3d-gmic: an efficient deep neural network to find small objects in large 3d images
An efficient deep neural network to find small objects in large 3D images
3D imaging enables accurate diagnosis by providing spatial information about organ
anatomy. However, using 3D images to train AI models is computationally challenging
because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained
with high-resolution 3D images, convolutional neural networks resort to downsampling them
or projecting them to 2D. We propose an effective alternative, a neural network that enables
efficient classification of full-resolution 3D medical images. Compared to off-the-shelf …
anatomy. However, using 3D images to train AI models is computationally challenging
because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained
with high-resolution 3D images, convolutional neural networks resort to downsampling them
or projecting them to 2D. We propose an effective alternative, a neural network that enables
efficient classification of full-resolution 3D medical images. Compared to off-the-shelf …
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