为了在 3D 医学图像上评估所提模型的一般性能,团队将 MedSAM-2 与 BTCV 多器官分割数据集上建立的先进分割方法进行了比较,包括知名的 nnUNET、TransUNet、UNetr、Swin-UNetr 模型以及 Diffusion-based 模型(如 EnsDiff、SegDiff 和 MedSegDiff)。此外团队还对原版 SAM,全微调 MedSAM、SAMed、SAM-Med2D、SAM-U、...
UNet由编码器和解码器两部分组成,通过跳跃连接(skip connections)来融合不同层次的信息。基于PyTorch实现的UNet模型代码示例,如何使用该模型进行数据集测试的流程。 1. UNet模型定义 importtorchimporttorch.nnasnnimporttorch.nn.functionalasFclassDoubleConv(nn.Module):"""(convolution => [BN] => ReLU) * 2"""...
Specifically, SAM2-UNet adopts the Hiera backbone of SAM2 as the encoder, while the decoder uses the classic U-shaped design. Additionally, adapters are inserted into the encoder to allow parameter-efficient fine-tuning. Preliminary experiments on various downstream tasks, such as camouflaged object...
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation - WZH0120/SAM2-UNet
通过使用自定义微调适配器,作者探索了SAM 2的性能上限,在BTCV数据集上实现了92.30%的Dice相似系数,超越了当前最先进的nnUNet模型12%。同时,作者通过研究各种提示生成器,解决了提示依赖性的问题。RFMedSAM 2: …
Image segmentation is one of the key factors in diagnosing glioma patients with brain tumors. It helps doctors identify the types of tumor that a patient is carrying and will lead to a prognosis that will help save the lives of patients. The analysis of medical images is a specialized domain...
Image segmentation is one of the key factors in diagnosing glioma patients with brain tumors. It helps doctors identify the types of tumor that a patient is carrying and will lead to a prognosis that will help save the lives of patients. The analysis of medical images is a specialized domain...
图像分割入门必学!UNet/DeeplabV3/Mask2former/SAM四 给大家整理了一份图像分割算法学习资料包 1,UNet/Deeplab/Mask2former/SAM/等图像分割算法源码资料 2,图像分割领域前沿顶会论文 3,图像分割学习路线图
图像分割入门必学!UNet/DeeplabV3/Mask2former/SAM四 给大家整理了一份图像分割算法学习资料包 1,UNet/Deeplab/Mask2former/SAM/等图像分割算法源码资料 2,图像分割领域前沿顶会论文 3,图像分割学习路线图
SAM2Rad achieves comparable performance to specialized models like UNet [1] and UNet++ [4] while providing greater flexibility and generalization (Table 5). By leveraging the SAM foundation model, SAM2Rad benefits from inherent robustness to diverse datasets and scenarios. The Prompt Predictor Networ...