Superparamagnetic nanohybrids with cross-linked polymers providing higher in vitro stability

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Cancer is among the leading causes of death worldwide, and as knowledge of the disease continues to grow there is an increasing interest towards precision medicine: more specifically towards the theranostics field, i.e the development of targeted molecular ...

BACKGROUND AND PURPOSE: MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This stud ...

Aims: Understanding the correlations between underlying medical and personal characteristics of a patient with cancer and the risk of lung metastasis may improve clinical management and outcomes. We used machine learning methodologies to predict the risk o ...

Sonosensitive perfluorocarbon F(8)TAC(18)-PFOB emulsion is under development to enhance heating, increase thermal contrast, and reduce treatment times during focused ultrasound tumor ablation of highly perfused tissue. The emulsion previously showed enhanc ...

Positron emission tomography is a nuclear imaging technique well known for its use in oncology for cancer diagnosis and staging. A PET scanner is a complex machine which comprises photodetectors placed in a ring configuration that detect gamma photons gen ...

BackgroundInterstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prom ...

BackgroundDetecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarge ...

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Harmonic nanoparticles (HNPs) have emerged as appealing exogenous probes for optical bioimaging due to their distinctive features such as long-term photostability and spectral flexibility, allowing multiphoton excitation in the classical (NIR-I) and extend ...

MRI is a non-invasive medical imaging modality that is sensitive to patient motion, which constitutes a major limitation in most clinical applications. Solutions may arise from the reduction of acquisition times or from motion-correction techniques, either ...

Molecular medical imaging is intended to increase the accuracy of diagnosis, particularly in cardiovascular and cancer-related diseases, where early detection could significantly increase the treatment success rate. In this study, we present mixed micelles ...

Among the medical imaging modalities, ultrasound (US) imaging is one of the safest, most widespread, and least expensive method used in medical diagnosis. In the past decades, several technological advances enabled the advent of ultrafast US imaging, an ac ...

Quantitative phase imaging (QPI) is an emerging label-free technique that produces images containing morphological and dynamical information without contrast agents. Unfortunately, the phase is wrapped in most imaging system. Phase unwrapping is the comput ...

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 ...

Optical imaging probes have played a major role in detecting and monitoring a variety of diseases. In particular, nonlinear optical imaging probes, such as second harmonic generating (SHG) nanoprobes, hold great promise as clinical contrast agents, as they ...

Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell. With ...

Cancer is a major health burden worldwide and the leading cause of death in industrialized countries. Early detection is a primary factor of survival and remission rate. Classical imaging methods such as magnetic resonance imaging, ultrasound imaging and m ...

Since the seventies, positron emission tomography (PET) has become an invaluable medical molecular imaging modality with an unprecedented sensitivity at the picomolar level, especially for cancer diagnosis and the monitoring of its response to therapy. Mor ...

High-throughput synchrotron-based tomographic microscopy at third generation light sources allows to probe cm-sized samples at micrometer-resolution. In this work, we present an approach to image a full mouse brain. With Indian-ink as a contrast agent, it ...

Magnetic resonance resonance (MRI) is a widely used modality to obtain in vivo tissue information. Clinical applications are near countless, and almost all body parts can be examined using an MR scanner. As the method is non invasive, does not use ionizing ...

Superparamagnetic nanohybrids with cross-linked polymers providing higher in vitro stability

Chattez avec Graph Search

Functionalization of harmonic nanoparticles for drug release and multimodal imaging applications

Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes

Medical and Personal Characteristics Can Predict the Risk of Lung Metastasis

Perfluorocarbon emulsion enhances MR-ARFI displacement and temperature in vitro: Evaluating the response with MRI, NMR, and hydrophone

Integrated electronics for time-of-flight positron emission tomography photodetectors

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study

A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Gd3+-Functionalized Lithium Niobate Nanoparticles for Dual Multiphoton and Magnetic Resonance Bioimaging

Choreography Controlled (ChoCo) brain MRI artifact generation for labeled motion-corrupted datasets

Vascular-targeted micelles as a specific MRI contrast agent for molecular imaging of fibrin clots and cancer cells

Ultrasound Imaging: From Physical Modeling to Deep Learning

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Biodegradable Harmonophores for Targeted High-Resolution In Vivo Tumor Imaging

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling To Machine Learning

Surface functionalization of metal oxide harmonic nanoparticles for targeted cancer imaging

Roadmap toward the 10 ps time-of-flight PET challenge

Brain micro-vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high-resolution phase-contrast X-ray tomography

Fat navigators based retrospective motion correction strategies for brain magnetic resonance imaging