4,035 Results Found

Multispectral live-cell imaging is an informative approach that permits detecting biological processes simultaneously in the spatial and temporal domain by exploiting spectrally distinct biosensors. However, the combination of fluorescent biosensors...

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the...

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunit...

In situ ATR-FTIR spectroscopy and imaging and image analysis were applied to the study of the multicomponent co-crystallization process involving S-valsartan and sacubitril in which LCZ696 crystals were formed. LCZ696 is a combination drug for use in...

Genetically engineered mouse models (GEMMs) and patient-derived xenograft mouse models (PDXs) can recapitulate important biological features of cancer. They are often part of precision medicine studies in a co-clinical setting, in which therapeutic i...

The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and cli...

(1) Background: Spinal cord injuries and diseases necessitate sophisticated tools for accurate diagnosis and treatment planning. However, the lack of reliable phantoms mimicking the complex structure of the spinal cord hinders the development and val...

Optical and SAR image registration and fusion are pivotal in the remote sensing field, as they leverage the complementary advantages of both modalities. However, achieving this with high accuracy and efficiency remains challenging. This challenge ari...

Zinc oxide (ZnO) and iron oxide (IO) nanoparticles have been identified as promising candidates for biomedical applications, based on their unique physicochemical properties. The association of these nanoparticles in a single system creates a bimodal...

Achieving a ^99mTc labeled thymidine radiotracer for single photon emission tomography (SPECT) is considered to be of interest. In this study, four novel thymidine analogs, 6a, 6b, 6c and 6d, were successfully synthesized via “click reaction” route an...

Due to its miniature size and single-pass nature, Unmanned Aerial Vehicle (UAV)-borne array synthetic aperture radar (SAR) is capable of obtaining three-dimensional (3D) electromagnetic scattering information with a low cost and high efficiency, maki...

A monolithic microfluidic free-flow electrophoresis device, fabricated using low-temperature co-fired ceramic technology, is presented. The device integrates gold electrodes and a 20 µm thick transparent ceramic optical window, suitable for flu...

The detection of heavy metal ions and organic pollutants from water sources remains critical challenges due to their detrimental effects on human health and the environment. Herein, a nitrogen and sulfur co-doped carbon quantum dot (NS-CQDs) fluoresc...

KOMPSAT-3, a Korean earth observing satellite, provides the panchromatic (PAN) band and four multispectral (MS) bands. They can be fused to obtain a pan-sharpened image of higher resolution in both the spectral and spatial domain, which is more infor...

For the co-saliency detection algorithm of an RGBD image that may have incomplete detection of common salient regions and unclear boundaries, we proposed an improved co-saliency detection method of RGBD images based on superpixels and hypergraphs. Fi...

Medical image segmentation has made significant progress when a large amount of labeled data are available. However, annotating medical image segmentation datasets is expensive due to the requirement of professional skills. Additionally, classes are...

Semi-supervised learning is a technique that utilizes a limited set of labeled data and a large amount of unlabeled data to overcome the challenges of obtaining a perfect dataset in deep learning, especially in medical image segmentation. The accurac...

Dimensionality reduction (DR) methods based on graph embedding are widely used for feature extraction. For these methods, the weighted graph plays a vital role in the process of DR because it can characterize the data’s structure information. M...

In December 2019, physicians reported numerous patients showing pneumonia of unknown origin in the Chinese region of Wuhan. Following the spreading of the infection over the world, The World Health Organization (WHO) on 11 March 2020 declared the nov...

With the development of social networks and intelligent terminals, it is becoming more convenient to share and acquire images. The massive growth of the number of social images makes people have higher demands for automatic image processing, especial...

Nonlinear and quantum optical devices based on periodically-poled thin film lithium niobate (PP-TFLN) have gained considerable interest lately, due to their significantly improved performance as compared to their bulk counterparts. Nevertheless, perf...

Image registration is the basis for the joint interpretation of synthetic aperture radar (SAR) and optical images. However, the significant nonlinear radiation difference (NRD) and the geometric imaging model difference render the registration quite...

Lately, deep learning technology has been extensively investigated for accelerating dynamic magnetic resonance (MR) imaging, with encouraging progresses achieved. However, without fully sampled reference data for training, the current approaches may...

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitati...

Fine-grained food image segmentation is essential for accurate dietary assessment and nutritional analysis, yet remains highly challenging due to ambiguous boundaries, inter-class similarity, and dense layouts of meals containing many different ingre...

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often causes severe viral pneumonia. Although many studies using mouse models have examined the pathogenicity of SARS-CoV-2, COVID-19 pathogenesis remains poorly understood. In vivo imaging...

As contemporary role models in the digital space, influencers are seen as one of the actors able to engage users with their posts, which also affects the image of a destination, and thus contributes to the co-creation process. At the same time, less...

This study based on co-occurrence analysis shearlet transform (CAST) effectively combines the latent low rank representation (LatLRR) and the regularization of zero-crossing counting in differences to fuse the heterogeneous images. First, the source...

The co-registration between SAR and optical images is a challenging task because of the speckle noise of SAR and the nonlinear radiation distortions (NRD), particularly in the one-look situation. In this paper, we propose a novel density descriptor b...

Aiming at the problem of misdetection caused by the traditional texture characteristic extraction model, which does not describe the correlation among multiple bands, an object-oriented remote sensing image change detection method based on a color co...

The Inverse Gas Chromatography (IGC) technique has been employed for the surface thermo-dynamic characterization of the polymer Poly(vinylidene chloride-co-acrylonitrile) (P(VDC-co-AN)) in its pure form. IGC attributes, such as London dispersive surf...

Universities play a significant role in the economic development of society as they provide knowledge and skills that are essential for social sustainability. In recent years, universities shifted their focus towards student-centered education and ne...

Geospatial co-registration is a mandatory prerequisite when dealing with remote sensing data. Inter- or intra-sensoral misregistration will negatively affect any subsequent image analysis, specifically when processing multi-sensoral or multi-temporal...

This research aims to examine the use of image processing and texture analysis to find a more reliable and efficient solution for identifying and classifying types of meat, based on their texture. The method used involves the use of feature extractio...

Background: This study aimed to analyze clinical and multimodal imaging characteristics of acute macular neuroretinopathy (AMN) post-recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods: Retrospective observational s...

Background and Purpose: Intracranial hemorrhage has been observed in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19), but the clinical, imaging, and pathophysiological features of intracranial bleeding...

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) us...

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and...

High uniformity of positron emission tomography (PET) images in the field of nuclear medicine is necessary to obtain excellent and stable data from the system. In this study, we aimed to apply and optimize a PET/magnetic resonance (MR) imaging system...

Multimodal image fusion and semantic segmentation play pivotal roles in autonomous driving and robotic systems, yet their inherent interdependence remains underexplored. To address this gap and overcome performance bottlenecks, we propose SC-CoSF, a...

COVID-19 is an ongoing, global pandemic caused by the novel, highly infectious SARS-CoV-2 virus. Efforts to mitigate the effects of SARS-CoV-2, such as mass vaccination and development of monoclonal therapeutics, require precise measurements of corre...

As the fastest growing trend in big data analysis, deep learning technology has proven to be both an unprecedented breakthrough and a powerful tool in many fields, particularly for image segmentation tasks. Nevertheless, most achievements depend on h...

Multi-modal remote sensing images often exhibit complex and nonlinear radiation differences which significantly hinder the performance of traditional feature-based image registration methods such as Scale-Invariant Feature Transform (SIFT). In contra...

Background/Objectives: Rhinophyma, an advanced form of rosacea, is characterized by significant nasal tissue enlargement and deformation, leading to aesthetic and psychosocial challenges. Traditional treatments are often invasive with variable outcom...

Neutralization assays have become an important tool since the beginning of the COVID-19 pandemic for testing vaccine responses and therapeutic antibodies as well as for monitoring humoral immunity to SARS-CoV-2 in epidemiological studies. The spike g...

In order to recognize breast cancer histopathological images, this article proposed a combined model consisting of a pyramid gray level co-occurrence matrix (PGLCM) feature extraction model and an incremental broad learning (IBL) classification model...

Thanks to the recent development of laser scanner hardware and the technology of dense image matching (DIM), the acquisition of three-dimensional (3D) point cloud data has become increasingly convenient. However, how to effectively combine 3D point c...

The application of ultra-high spatial resolution imagery from small unpiloted aerial systems (sUAS) can provide valuable information about the status of built infrastructure following natural disasters. This study employs three methods for improving...

(1) Background: Chest Computed Tomography (CT) has been proposed as a non-invasive method for confirming the diagnosis of SARS-CoV-2 patients using radiomic features (RFs) and baseline clinical data. The performance of Machine Learning (ML) methods u...

Background/Objectives: Accurate diagnosis during ultrasound examinations of patients with kidney and gallbladder stones is crucial. Although stone areas typically show posterior acoustic shadowing on ultrasound images, their accurate diagnosis can be...