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ConTNet: cross attention convolution and transformer for aneurysm image segmentation.

, , , , , , and . BIBM, page 3618-3625. IEEE, (2023)

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DCAU-Net: dense convolutional attention U-Net for segmentation of intracranial aneurysm images., , , , and . Vis. Comput. Ind. Biomed. Art, 5 (1): 9 (2022)A novel feature extraction approach based on neighborhood rough set and PCA for migraine rs-fMRI., , , and . J. Intell. Fuzzy Syst., 38 (5): 5731-5741 (2020)A histogram-driven generative adversarial network for brain MRI to CT synthesis., , , , and . Knowl. Based Syst., (October 2023)An end-to-end model for ECG signals classification based on residual attention network., , , , and . Biomed. Signal Process. Control., 80 (Part): 104369 (2023)CRANet: a comprehensive residual attention network for intracranial aneurysm image classification., , , and . BMC Bioinform., 23 (1): 322 (2022)Identifying depression disorder using multi-view high-order brain function network derived from electroencephalography signal., , , , , , and . Frontiers Comput. Neurosci., (2022)Comparative analysis of U-Net and TLMDB GAN for the cardiovascular segmentation of the ventricles in the heart., , , and . Comput. Methods Programs Biomed., (2022)Feature Enhanced and Context Inference Network for Pancreas Segmentation., , , and . BIC-TA (2), volume 1566 of Communications in Computer and Information Science, page 244-257. Springer, (2021)Correction: DCAU-Net: dense convolutional attention U-Net for segmentation of intracranial aneurysm images., , , , and . Vis. Comput. Ind. Biomed. Art, 5 (1): 12 (2022)ConTNet: cross attention convolution and transformer for aneurysm image segmentation., , , , , , and . BIBM, page 3618-3625. IEEE, (2023)