141 citations · 179 across the 10 of their papers we have counts for
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CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
Ange Lou, Shuyue Guan, Murray Loew
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment. It is a challenging task because of the wide variety of objects' sizes, shapes,…
Informing selection of performance metrics for medical image segmentation evaluation using configurable synthetic errors
Shuyue Guan, Ravi K. Samala, Weijie Chen
Machine learning-based segmentation in medical imaging is widely used in clinical applications from diagnostics to radiotherapy treatment planning. Segmented medical images with gr…
A Sneak Attack on Segmentation of Medical Images Using Deep Neural Network Classifiers
Shuyue Guan, Murray Loew
Instead of using current deep-learning segmentation models (like the UNet and variants), we approach the segmentation problem using trained Convolutional Neural Network (CNN) class…
CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
Ange Lou, Shuyue Guan, Hanseok Ko +1
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment. It is a challenging task because of the wide variety of objects' sizes, shapes,…
Segmentation of Infrared Breast Images Using MultiResUnet Neural Network
Ange Lou, Shuyue Guan, Nada Kamona +1
Breast cancer is the second leading cause of death for women in the U.S. Early detection of breast cancer is key to higher survival rates of breast cancer patients. We are investig…
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation
Ange Lou, Shuyue Guan, Murray Loew
Recently, deep learning has become much more popular in computer vision area. The Convolution Neural Network (CNN) has brought a breakthrough in images segmentation areas, especial…