Abstract: Medical image segmentation is essential for clinical diagnosis and treatment planning. Existing segmentation methods encounter challenges such as managing size variations, interpreting ...
Abstract: CNNs have demonstrated superior performance in medical image segmentation. To overcome the limitation of only using local receptive field, previous work has attempted to integrate ...
A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
This project leverages U-Net for lung region segmentation and CNN for cancer classification using CT scan images. It aims to enhance lung cancer detection accuracy through deep learning techniques.
Shipments of five scanners per quarter starting on Q1’26 for total revenue of approximately $33 million over three years NOVATO, Calif.--(BUSINESS WIRE)--QT Imaging Holdings, Inc. (“QTI” or the ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback