(2024). Cross-Modality Cardiac Insight Transfer: A Contrastive Learning Approach to Enrich ECG with CMR Features. In: Linguraru, M.G., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes in Computer Science, vol 15003. Springer, Cham....
We present a cross-modality generation framework that learns to generate translated modalities from given modalities in MR images. Our proposed method performs Image Modality Translation (abbreviated as IMT) by means of a deep learning model that leverag
同时为了减少特征冗余以及增强跨模态特征关联,在编解码器之间插入Refifinement Middleware, 通过cross-modality weighting refifinement (cmWR) unit 和self-modality Attention refifinement (smAR) unit。在分支设计方面,作者通过综合之前的方法,采用了一种新的分支结构设计j:即RGB分支,Depth分支以及由这两个分支渐进引...
Each modality’s features serve as queries to the other’s feature space, enabling a more comprehensive understanding of the interdependencies and relationships between the modalities. As shown in Fig. 5, this module comprises two main components: cross-modal attention (CMT) and cross-channel ...
Specifically, we treat missing modalities also as masked modalities, and employ a strategy similar to Masked Autoencoder (MAE) to learn feature-to-feature reconstruction across arbitrary modality combinations. The reconstructed features for missing modalities act as supplements to form approximate modality...
relationships within a single type of data modality, such as the various visual features within an image. Inter-modal interactions involve relationships between different types of data modalities, such as visual and linguistic features. Contemporary image captioning methods have advanced in integrating ...
Cross-modal binding thereby expands the KCs representing the memory engram for each modality into those representing the other. This broadening of the engram improves memory performance after multisensory learning and permits a single sensory feature to retrieve the memory of the multimodal experience....
Paper tables with annotated results for CMTR: Cross-modality Transformer for Visible-infrared Person Re-identification
This paper introduces a versatile adaptation of the nnU-Net framework as a robust baseline for both cross-modality synthesis and image inpainting tasks. Known for its superior performance in segmentation challenges, nnU-Net's automatic configuration and parameter optimization capabilities have been ...
Magneto-Acousto-Electrical Tomography (MAET) is a multi-physics coupling imaging modality that integrates the high resolution of ultrasound imaging with th... S Bu,Y Li,W Ren,... - 《Electronic Research Archive》 被引量: 0发表: 2023年 DCAN: Deep Consecutive Attention Network for Video Super...