Artificial intelligence for image registration in radiation oncology
Automatic image registration plays an important role in many aspects of the radiation
oncology workflow ranging from treatment simulation, image guided and adaptive …
oncology workflow ranging from treatment simulation, image guided and adaptive …
Adversarial uni-and multi-modal stream networks for multimodal image registration
Deformable image registration between Computed Tomography (CT) images and Magnetic
Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we …
Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we …
SymReg-GAN: symmetric image registration with generative adversarial networks
Symmetric image registration estimates bi-directional spatial transformations between
images while enforcing an inverse-consistency. Its capability of eliminating bias introduced …
images while enforcing an inverse-consistency. Its capability of eliminating bias introduced …
Image registration: Maximum likelihood, minimum entropy and deep learning
In this work, we propose a theoretical framework based on maximum profile likelihood for
pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that …
pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that …
Multimodal priors guided segmentation of liver lesions in MRI using mutual information based graph co-attention networks
S Mo, M Cai, L Lin, R Tong, Q Chen, F Wang… - … Image Computing and …, 2020 - Springer
Segmentation of focal liver lesions serves as an essential preprocessing step for initial
diagnosis, stage differentiation, and post-treatment efficacy evaluation. Multimodal MRI …
diagnosis, stage differentiation, and post-treatment efficacy evaluation. Multimodal MRI …
Mutual information-based graph co-attention networks for multimodal prior-guided magnetic resonance imaging segmentation
S Mo, M Cai, L Lin, R Tong, Q Chen… - … on Circuits and …, 2021 - ieeexplore.ieee.org
Multimodal magnetic resonance imaging (MRI) provides complementary information about
targets, and the segmentation of multimodal MRI is widely used as an essential …
targets, and the segmentation of multimodal MRI is widely used as an essential …
Probabilistic image registration via deep multi-class classification: characterizing uncertainty
We present a novel approach to probabilistic image registration that leverages the strengths
of deep-learning for modeling agreement between images. We use a deep multi-class …
of deep-learning for modeling agreement between images. We use a deep multi-class …
On the applicability of registration uncertainty
Estimating the uncertainty in (probabilistic) image registration enables, eg, surgeons to
assess the operative risk based on the trustworthiness of the registered image data. If …
assess the operative risk based on the trustworthiness of the registered image data. If …
[PDF][PDF] 多模态图像引导手术导航进展
杨健， 王媛媛， 艾丹妮， 宋红， 范敬凡， 付天宇… - Acta Optica …, 2023 - researching.cn
摘要手术导航综合运用器官分割建模与手术规划, 位姿标定与跟踪定位, 多模态图像配准与融合
显示等技术, 使医生精确定位病灶与手术工具的位置, 透过组织表面对内部组织进行观测 …
显示等技术, 使医生精确定位病灶与手术工具的位置, 透过组织表面对内部组织进行观测 …
Unimodal cyclic regularization for training multimodal image registration networks
The loss function of an unsupervised multimodal image registration framework has two
terms, ie, a metric for similarity measure and regularization. In the deep learning era …
terms, ie, a metric for similarity measure and regularization. In the deep learning era …