Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

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Background: Fetal brain MRI is increasingly used to complement ultrasound imaging. Images are processed using complex super-resolution reconstruction pipelines, which may bias biometric and volumetric measurements. Objective: To assess the consistency of 2 ...

Noninvasive tracking of biochemical processes in the body is paramount in diagnostic medicine. Among the leading techniques is spectroscopic magnetic resonance imaging (MRI), which tracks metabolites with an amplified (hyperpolarized) magnetization signal ...

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Volume electron microscopy is the method of choice for the in situ interrogation of cellular ultrastructure at the nanometer scale, and with the increase in large raw image datasets generated, improving computational strategies for image segmentation and s ...

Compressive Raman imaging has emerged as a promising technique to speed up chemical imaging by compressing the data during acquisition. Yet, current scanning imaging speed is fundamentally limited by the sensors pixel dwell times of at best 1µs. Here, we i ...

Neurodegenerative and neuroinflammatory disorders often involve complex pathophysiological mechanisms that are â to this date â only partially understood. A more comprehensive understanding of those microstructural processes and their characterization ...

Microcomputed tomography (mu CT) is a nondestructive X-ray imaging method used in plant physiology to visualize in situ plant tissues that enables assessments of embolized xylem vessels. Whereas evidence for X-ray-induced cellular damage has been reported, ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, where some objects occupy more pixels than others. This causes traditional eva ...

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 ...

Liquids confined down to the atomic scale can show radically new properties. However, only indirect and ensemble measurements operate in such extreme confinement, calling for novel optical approaches that enable direct imaging at the molecular level. Here ...

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing s ...

The successes of deep learning for semantic segmentation can in be, in part, attributed to its scale: a notion that encapsulates the largeness of these computational architectures and the labeled datasets they are trained on. These resource requirements hi ...

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolut ...

Visual affordance segmentation identifies the surfaces of an object an agent can interact with. Common challenges for the identification of affordances are the variety of the geometry and physical properties of these surfaces as well as occlusions. In this ...

Dense image-based prediction methods have advanced tremendously in recent years. Their remarkable development has been possible due to the ample availability of real-world imagery. While these methods work well on photographs, their abilities do not genera ...

A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representation of the data where information irrelevant to the task is lost. For image da ...

Medipix4 is the latest member in the Medipix/Timepix family of pixel detector chips aimed at high rate spectroscopic X-ray imaging using high-Z materials. The chip address the limitations of conventional hybrid pixel detectors for X-ray imaging. Its predec ...

Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

Chattez avec Graph Search

Biometry and volumetry in multi-centric fetal brain magnetic resonance imaging: assessing the bias of super-resolution reconstruction

Long-lived enhanced magnetization-A practical metabolic MRI contrast material

The role of computational methods in cardiovascular medicine: a narrative review

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Towards video-rate compressive spontaneous Raman imaging using single-photon avalanche diode arrays

Development and clinical validation of computational imaging biomarkers for neurodegenerative diseases

In vivo X-ray microtomography locally affects stem radial growth with no immediate physiological impact

Aggregating Spatial and Photometric Context for Photometric Stereo

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Parallelized compressive spontaneous Raman imaging via SPAD arrays (Conference Presentation)

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union

Functional neuroimaging options for tinnitus

Liquid-activated quantum emission from native hBN defects for nanofluidic sensing

Correlated-photon imaging at 10 volumetric images per second

Confidence Matters: Applications to Semantic Segmentation

Multi-site, Multi-domain Airway Tree Modeling

Affordance segmentation of hand-occluded containers from exocentric images

Dense Image-based Predictions for Comics Analysis

How deep convolutional neural networks lose spatial information with training

Medipix4, a high granularity four sides buttable pixel readout chip for high resolution spectroscopic X-ray imaging at rates compatible with medical CT scans