Related papers: Characterizing visual cortical magnification with …
Measuring personal head-related transfer functions (HRTFs) is essential in binaural audio. Personal HRTFs are not only required for binaural rendering and for loudspeaker-based binaural reproduction using crosstalk cancellation, but they…
The universal scaling law of cortical morphology describes cortical folding as the covariance of average grey matter thickness, pial surface area, and exposed surface area. It applies for mammalian species, humans, and across lobes, however…
The Trail Making Test (TMT) is one of the most popular neuropsychological tests in the clinical assessment of executive functions (EF) and research in a wide range of clinical conditions. In addition to its sensitivity to executive…
Multi-focus image fusion (MFF) is a popular technique to generate an all-in-focus image, where all objects in the scene are sharp. However, existing methods pay little attention to defocus spread effects of the real-world multi-focus…
Surface-based cortical analysis is valuable for a variety of neuroimaging tasks, such as spatial normalization, parcellation, and gray matter (GM) thickness estimation. However, most tools for estimating cortical surfaces work exclusively…
This paper attacks an emerging challenge of multi-modal retinal disease recognition. Given a multi-modal case consisting of a color fundus photo (CFP) and an array of OCT B-scan images acquired during an eye examination, we aim to build a…
We proposed a fusion mechanism for the distributed cooperative map matching (CMM) within the vehicular ad-hoc network. This mechanism makes the information from each node reachable within the network by other nodes without direct…
Modern autonomous vehicles and robots utilize versatile sensors for localization and mapping. The fidelity of these maps is paramount, as an accurate environmental representation is a prerequisite for stable and precise localization. Factor…
Prompt learning has become one of the most efficient paradigms for adapting large pre-trained vision-language models to downstream tasks. Current state-of-the-art methods, like CoOp and ProDA, tend to adopt soft prompts to learn an…
We present a hybrid method that performs the complete parcellation of the cerebral cortex of an individual, based on the connectivity information of the white matter fibers from a whole-brain tractography dataset. The method consists of…
Three-dimensional reconstruction of cortical surfaces from MRI for morphometric analysis is fundamental for understanding brain structure. While high-field MRI (HF-MRI) is standard in research and clinical settings, its limited availability…
In this paper, we present a novel region-based segmentation method for cortical spreading depressions in 2-photon microscopy images. Fluorescent microscopy has become an important tool in neuroscience, but segmentation approaches are…
Retinal fundus photography enhancement is important for diagnosing and monitoring retinal diseases. However, early approaches to retinal image enhancement, such as those based on Generative Adversarial Networks (GANs), often struggle to…
Non-negative matrix factorization (NMF) has proved effective in many clustering and classification tasks. The classic ways to measure the errors between the original and the reconstructed matrix are $l_2$ distance or Kullback-Leibler (KL)…
In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable. For this, neuroscientists rely on basic methods such as…
When using an electron microscope for imaging of particles embedded in vitreous ice, the objective lens will inevitably corrupt the projection images. This corruption manifests as a band-pass filter on the micrograph. In addition, it causes…
Vision Transformers (ViT) have made many breakthroughs in computer vision tasks. However, considerable redundancy arises in the spatial dimension of an input image, leading to massive computational costs. Therefore, We propose a…
Precise segmentation of retinal arteries and veins carries the diagnosis of systemic cardiovascular conditions. However, standard convolutional architectures often yield topologically disjointed segmentations, characterized by gaps and…
In this letter, we propose a modulation classification algorithm which is based on the received signal's amplitude for coherent optical receivers. The proposed algorithm classifies the modulation format from several possible candidates by…
Quantitative descriptors convert high-dimensional medical images into low-dimensional features capable of differentiating organ shapes that correlate with injury or disease progression for diagnostic purposes. An important example is aortic…