IMOP-lab / U-Shaped-Connection Star 18 Code Issues Pull requests [NeurIPS 2024] Upping the Game: How 2D U-Net Skip Connection Flipping 3D Segmentation medicalimageanalysis imagesegmentation skipconnection 2du-net Updated Nov 1, 2024 Python Improve this page Add a description, image, and...
U-Net+Transformer感觉应该是可以的，可以考虑做相关的对比消融实验，U-Net+Transformer在stable diffusion...
# conv6 = ConvLSTM2D(512, 3, activation='relu', padding='same', kernel_initializer='he_normal', return_sequences=True)(conv6) # up7 = ConvLSTM2D(256, 2, activation='relu', padding='same', kernel_initializer='he_normal', return_sequences=True)( # TimeDistributed(UpSampling2D(size=(2...
et al. Using 2D U-Net convolutional neural networks for automatic acetabular and proximal femur segmentation of hip MRI images and morphological quantification: a preliminary study in DDH. BioMed Eng OnLine 23, 98 (2024). https://doi.org/10.1186/s12938-024-01291-3 Download citation Received11 ...
ConvLSTM2D能够更好地理解图像中的上下文信息，这对于医学图像分割等任务尤为重要。通过使用TimeDistributed包装器，ConvLSTM2D层能够独立处理输入序列中的每个图像帧，提取出每个帧的特征。Bidirectional包装器允许网络学习未来帧的信息，这在需要预测序列变化或依赖于时间顺序的场景中非常有用。模型性能的提升：实...
U-Net在医学图像分割中的应用，结合CNN和ConvLSTM2D，是近年来深度学习领域的一个重要进展。这项技术首先在2018年的MICCAI会议上提出，通过在普通的U-Net结构中加入ConvLSTM2D层，以增强网络在处理具有时空依赖性的医学图像时的能力。这种结合不仅提高了特征提取的全面性，还允许网络更好地学习和捕捉图像中...
2du.net服务器iP: 当前解析: 子域名查询备案查询Whois 历史解析记录: 2023-05-26---2025-01-24127.0.0.1 2022-10-31---2023-02-20114.67.182.72 2021-01-07---2022-05-18222.186.184.3 2021-01-07---2022-05-18111.225.218.3 2021-12-12---2022-05-18119.188.208.2 2021-12-12---...
发现最基本的网络模型还是U-Net，也搜到了一些用纯transformer做细胞核图像分割的文章，但是没有看到U-...
2.5. Fully automated lumbar bone marrow segmentation using 2D U-Net The lumbar spinal T1-weighted MRI of each subject was resampled to have identical image sizes across all subjects, and pixel values were normalized between 0 and 1. The mask images, which contain binary images with manually seg...
In the first stage, a 2D U-Net model coupled with the iterative randomized Hough transform is employed on the balanced-steady state free precession (bSSFP) MR sequences, so as to find the center coordinates of the left ventricles (LVs). The regions of interest (ROIs) are then localized ...