我们的模型RegGAN,将misaligned target image考虑为noisy label,这意味者问题变为使用noisy label的监督学习; 我们的贡献如下: (1)我们从loss-correction理论印证了RegGAN的可行性;具体来说我们训练了一个具有额外配准网络的生成器,全局寻找对于image-to-iamge translation和registraztion task的公共最优解 (2.)RegGAN...
Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific architectures or require refinement through non-end-to-end...
Our model demonstrated successful image synthesis across various modalities even allowing for one-to-many modality translations. Furthermore, it outperformed other one-to-one translation models in quantitative evaluations. 展开 关键词: Adaptation models Solid modeling Three-dimensional displays Image ...
37 Nucleus-Aware Self-Supervised Pretraining Using Unpaired Image-to-Image Translation for Histopathology Images 摘要:自监督预训练试图通过从未标记数据中获取有效特征来提高模型性能,并在组织病理学图像领域证明了其有效性。尽管它取得了成功,但很少有研究专注于提取对病理分析至关重要的核水平信息。在这项工作中...
今天要跟大家分享的是关于医学图像分割方法的综述,我们将翻译一篇2020年的医学图像分割综述文章,题为“Medical Image Segmentation Using Deep Learning: A Survey”,该文章介绍了深度学习在医学图像分割领域的应用和发展情况。 一、简介(一)医学图像分割 一般的图像分割任务主要有两类:语义分割(semantic segmentation)和...
Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study [Jonghun Kim], [Hyunjin Park] Department of Electrical and Computer Engineering Sungkyunkwan University, Suwon, Korea WACV 2024[paper][arxiv] ...
image-to-image translation stroke lesion segmentation image synthesis 1. Introduction Ischemic stroke (IS) is the second leading cause of death worldwide [1], and, if not fatal, frequently results in irreversible brain tissue damage and disabilities. IS is caused by occlusion of blood vessels, ...
The UNIT consists of one generator and two discriminators. The generator performs image-to-image translation from low dose to high dose. The discriminators are PatchGAN networks that return the patch-wise probability that the input data is real or generated. One discriminator distinguishes between ...
The proposed model for automatic clinical image caption generation combines the analysis of radiological scans with structured patient information from the textual records. It uses two language models, the Show-Attend-Tell and the GPT-3, to generate comprehensive and descriptive radiology records. The ...
Current medical image translation is implemented in the image domain. Considering the medical image acquisition is essentially a temporally continuous process, we attempt to develop a novel image translation framework via deep learning trained in video domain for generating synthesized computed tomography (...