swin-transformer讲解:https://www.bilibili.com/video/BV1pL4y1v7jCswin-unetr: https://github.com/Project-MONAI/research-contributions/tree/master/SwinUNETR/BRATS21, 视频播放量 3463、弹幕量 0、点赞数 16、投硬币枚数 8、收藏人数 70、转发人数 7, 视频作者 青梅
conda create -n 新环境名 --clone旧环境名 这里我们的环境名就叫 swinunetr ,这样就不会乱啦~~~ 一切都准备就绪之后,我们就去看官网啦,Swin UNETR 有 BTCV (CT)和 BTS2021 (MRI)两种,这里我用的是 BTCV ,因为我自己的数据集是 CT 的。 因为官网里面没有告诉我们 dataset 的架构,所以我用的还是之前 ...
本篇文章和上一篇Swin-Unet类似,利用Transformer 提出了用于brain tumor的分割方法 -Swin UNETR。 Method 网络结构和U-Net 类似,主要使用的是Swin Transformer Block和Swin-Unet中的编码器类似,只不过输入数据是3D 的MR 图像。需要注意的是Swin Transformer 中的 W-MSA和SW-MSA均在3维图像上计算,如下图所示。
受视觉转换器及其变体成功的启发,我们提出了一种新颖的分割模型,称为 Swin UNET TRansformers (Swin UNETR)。具体来说,将 3D 脑肿瘤语义分割任务重新表述为序列到序列预测问题,其中多模态输入数据被投影到 1D 嵌入序列中,并用作分层 Swin 变换器的输入作为编码器。 swin 转换器编码器通过利用移位窗口计算自注意力...
Inspired by the success of vision transformers and their variants, we propose a novel segmentation model termed Swin UNEt TRansformers (Swin UNETR). Specifically, the task of 3D brain tumor semantic segmentation is reformulated as a sequence to sequence prediction problem wherein multi-modal input ...
nohup tensorboard --port 6007 --logdir /root/autodl-tmp/SwinUNETR/runs& cache_rate是用来控制缓存数据的。如果被kill了,就加上--use_normal_dataset num_samples就当batch_siz --workers 0不要删。 val_every是多少epoch validation一次。每次validation都会保存一次模型 ...
[MICCAI 2023] Continual Learning for Abdominal Multi-Organ and Tumor Segmentation - ContinualLearning/model/swinunetr.py at main · gkw0010/ContinualLearning
Objective: To distinguish infarct location and type with the utmost precision using the advantages of the Swin UNEt TRansformers (Swin UNETR) architecture. Methods: The research employed a two-phase training approach. In the first phase, the Swin UNETR model was trained using the Isc...
The present study aimed to enhance subject-specific knee joint FE modeling by incorporating a semi-automated segmentation algorithm using a 3D Swin UNETR for an initial segmentation of the femur and tibia, followed by a statistical shape model (SSM) adjustment to improve surface roughness and ...
We employ CPS to enhance the state-of-the-art SwinUNETR model for medical image segmentation, initially pre-trained on the BraTs2021 dataset, this enhanced model is subsequently applied to three hippocampal datasets. The results reveal that CPS significantly outperforms existing methods, increasing ...