In this paper, we give an overview of deep learning-based approaches for multi-modal medical image segmentation task. Firstly, we introduce the general principle of deep learning and multi-modal medical image segmentation. Secondly, we present different deep learning network architectures, then ...
Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation 1. 提纲 多模态数据能够改善切割半监督医学图像的效果,但是处理相应多模态数据的模型大多高度集成,而且这些数据同时应用于训练和推演的问题限制了临床医学事件实践。 为此,作者提出了半监督-对比共存...
Image segmentation is a challenging task in visual media reasoning. Due to the development of medical imaging equipment, intelligent visual computing over multi-modal data to assist clinical diagnosis has attracted public attention in medical field. Multimodal medical image segmentation lays the ground fo...
In recent years, there have been several solutions to medical image segmentation, such as U-shaped structure, transformer-based network, and multi-scale feature learning method. However, their network parameters and real-time performance are often neglected and cannot segment boundary regions well. Th...
Projects Security Insights Additional navigation options main 1Branch0Tags Code README Apache-2.0 license 🔥PASSION [ACM MM'24 Oral]🎉 PASSION:Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates Junjie Shi1,Caozhi Shang1,Zhaobin Sun1,Li Yu1,Xin Yang...
In: Proceedings of international conference on medical image computing and computer-assisted intervention. Springer, pp 234–241. https://doi.org/10.1007/978-3-319-24574-4_28 Fang L, Wang X, Wang L (2020) Multi-modal medical image segmentation based on vector-valued active contour models. ...
Medical image segmentation is challenging due to the need for expert annotations and the variability of these manually created labels. Previous methods tackling label variability focus on 2D segmentation and single modalities, but reliable 3D multi-modal approaches are necessary for clinical applications ...
Semi-Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation - nusdbsystem/SSUMML
PH-Net: Semi-Supervised Breast Lesion Segmentation via Patch-wise Hardness. [Paper][Code][Video] Image Generation (图像生成) Learned representation-guided diffusion models for large-image generation. [Paper] MedM2G: Unifying Medical Multi-Modal Generation via Cross-Guided Diffusion with Visual Invarian...
To solve the above problems, a dual-scale multi-modality perceptual generative adversarial network (DualMMP-GAN) is proposed for medical image segmentation based on CycleGAN. Firstly, DualMMP-GAN is proposed for multi-modality MR medical image generation (T1-to-Flair generation, Flair-to-T1 genera...