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eess.IV2022★ 2 cited
Synthetic Tumors Make AI Segment Tumors Better
Qixin Hu, Junfei Xiao, Yixiong Chen +4
We develop a novel strategy to generate synthetic tumors. Unlike existing works, the tumors generated by our strategy have two intriguing advantages: (1) realistic in shape and tex…
eess.IV2021
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation
Hu Cao, Yueyue Wang, Joy Chen +4
In the past few years, convolutional neural networks (CNNs) have achieved milestones in medical image analysis. Especially, the deep neural networks based on U-shaped architecture…
eess.IV2021★ 35 cited
SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation
Boxiang Yun, Yan Wang, Jieneng Chen +3
Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety of applications relied on high-precision pathology image segmentation, such as computational pathology and…