Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images

Volume: 93, Pages: 101975 - 101975
Published: Oct 1, 2021
Abstract
Image segmentation remains to be one of the most vital tasks in the area of computer vision and more so in the case of medical image processing. Image segmentation quality is the main metric that is often considered with memory and computation efficiency overlooked, limiting the use of power hungry models for practical use. In this paper, we propose a novel framework (Kidney-SegNet) that combines the effectiveness of an attention based...
Paper Details
Title
Efficient deep learning architecture with dimension-wise pyramid pooling for nuclei segmentation of histopathology images
Published Date
Oct 1, 2021
Volume
93
Pages
101975 - 101975
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