… of multi-modal data involves automatically estimating the coordinate transformation required
to align the multi-modal image … on matching local-frequency image representations, which …

… , multimodal image … image-to-image (I2I) translation in computer vision applications and its
growing use in biomedical areas provide a tempting possibility of transforming the multimodal …

… by techniques of computer vision and artificial intelligence, to achieve integration of
multimodality imaging information and expert medical knowledge [l I. Computer networks will also …

… We first trained unimodal baseline models on images alone and non-image data alone.
We then developed three multimodal fusion models that learn jointly from image and non-image …

… In this work, we focus on one exemplar application of interventional multimodal image
registration which is to register pre-procedural multi-parametric magnetic resonance (MR) images …

… They provide superior results in comparison to individual CT or MRI images. Multiscale
transforms (MSTs) are widely used in fusing multimodal images like CT and MRI. However, they …

… computer vision and medical imaging… image similarities between multimodal images due
to their difference in appearance and/or signal expression. In [58] internal similarities in images …

… image on the left was generated using Sun Vision, and clearly shows a vessel running along
the medial aspect of the tumor. The image on the right was generated using our multimodal …

… computer vision techniques, machine learning, and imaging instruments eg, visible-light or
color imaging and hyperspectral imaging. … multimodal deep learning and multimodal imaging …

… Abstract—Recently, dense connections have attracted substantial attention in computer
vision because they facilitate gradient flow and implicit deep supervision during training. …