Artificial intelligence (AI) in research histopathology is turning whole-slide images of preclinical tissue into structured, quantitative data rather than a pathologist's subjective impression alone.
@article{jungsuperpixel, title={Superpixel-based Graph Convolutional Network for Semantic Segmentation}, author={Jung, Hoin and Park, Seong Yeon and Yang, Su and Kim, Jin} } Thie repository is an ...
Abstract: Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based methods often ...
Three-dimensional (3D) liver tumor segmentation from Computed Tomography (CT) images is a prerequisite for computer-aided diagnosis, treatment planning, and monitoring of liver cancer. Despite many ...
Diet plays an important role in people’s daily life with its strong correlation to health and chronic diseases. Meanwhile, deep based food computing emerges to provide lots of works which including ...
Abstract: Deep convolutional neural network (CNN), although recognized to be considerably successful in its application to semantic segmentation, is inadequate for extracting the overall structure ...
Deep learning neural networks are especially potent at dealing with structured data, such as images and volumes. Both modified LiviaNET and HyperDense-Net performed well at a prior competition ...
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