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Background: The pathophysiology behind tinnitus is still not well understood. Different imaging methods help in the understanding of the complex relationships that lead to the perception of tinnitus.Objective: Herein, different functional imaging methods t ...
Today, Magnetic Resonance Imaging (MRI) is a well-established medical imaging modality thanks to its excellent soft tissue contrast. Conventional MR image contrasts can be weighted towards one or more physical properties that discriminate different tissues ...
Imaging the inner ear microanatomy is of great importance for the assessment of the state of the cells responsible for sound detection. Hearing disorders are mainly due to a malfunction of the cochlea, the bone containing the cells inside the inner ear. Un ...
The study describes a comprehensive methodology to evaluate X-Ray micro-computed tomography data from sand samples and to characterize their 3D microstructural properties. Fine and medium-grained sands are analyzed in their natural and bio-cemented states. ...
SPRINGER2023
Far field superlensing of light has generated great attention in optical focusing and imaging applications. The capability of metamaterials to convert evanescent waves to propagative waves has led to numerous proposals in this regard. The common drawback o ...
We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vis ...
A broad class of imaging modalities involve the resolution of an inverse-scattering problem. Among them, three-dimensional optical diffraction tomography (ODT) comes with its own challenges. These include a limited range of views, a large size of the sampl ...
2020
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Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...
Clinical applications, such as image-guided surgery and noninvasive diagnosis, rely heavily on multi-modal images. Medical image fusion plays a central role by integrating information from multiple sources into a single, more understandable output. We prop ...
Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...
