We report a multi-mode compact microscope (MCM) for high-contrast and high-resolution imaging. The MCM consists of two LED illuminations, a magnification lens, a lift stage, and a housing with image processing and LED control boards. The MCM allows m...
This paper proposes a new cross-hole tomography imaging (CTI) method for variable-depth defects in metal plates based on multi-mode electromagnetic ultrasonic Lamb waves (LWs). The dispersion characteristics determine that different modes of LWs are...
Background: With the guidance of multi-mode imaging, the time window for endovascular thrombectomy (EVT) has been expanded to 24 h. However, poor clinical outcomes are still not uncommon. We aimed to develop a multi-mode imaging scale for endovascula...
In this work, we develop a multi-mode microscopic hyperspectral imager (MMHI) for the detection of biological samples in transmission imaging, reflection imaging and fluorescence mode. A hyperspectral image cube can be obtained with 5 μm spatial r...
In this paper, a novel medical image encryption method based on multi-mode synchronization of hyper-chaotic systems is presented. The synchronization of hyper-chaotic systems is of great significance in secure communication tasks such as encryption o...
In this paper, we present a multi-resolution mode CMOS image sensor (CIS) for intelligent surveillance system (ISS) applications. A low column fixed-pattern noise (CFPN) comparator is proposed in 8-bit two-step single-slope analog-to-digital converte...
Owing to its high reliability and accuracy, the ratiometric luminescent thermometer can provide non-contact and fast temperature measurements. In particular, the nanomaterials doped with lanthanide ions can achieve multi-mode luminescence and tempera...
A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univaria...
Electromagnetic vortex waves have received widespread attention in many fields due to their unique physical characteristics. The information dimension provided by vortex electromagnetic waves brings possibilities for future breakthroughs in radar det...
The GaoFen-3 (GF-3) satellite is the only synthetic aperture radar (SAR) satellite in the High-Resolution Earth Observation System Project, which is the first C-band full-polarization SAR satellite in China. In this paper, we proposed some error sour...
There are several image inverse tasks, such as inpainting or super-resolution, which can be solved using deep internal learning, a paradigm that involves employing deep neural networks to find a solution by learning from the sample itself rather than...
Nanomaterials extensively studied by nanotechnology scientists have been extensively applied in biomedicine, chemistry, physics and other fields nowadays. Magnetic nanoparticles, surpassing nano applications, are found to possess many advantages over...
This paper aims to develop an activity recognition algorithm to allow parents to monitor their children at home after school. A common method used to analyze electroencephalograms is to use infinite impulse response filters to decompose the electroen...
In response to the challenges of karst geophysical exploration in an environment with strong external interference, this paper proposes a new method, namely the frequency-Bessel transform method, for extracting multi-order dispersion curves of surfac...
In multi-modal images (MMI), the differences in their imaging mechanisms lead to large signal-to-noise ratio differences, which means that the matching of geometric invariance and the matching accuracy of the matching algorithms often cannot be balan...
Nuclear imaging techniques, primarily including positron emission tomography and single-photon emission computed tomography, can provide quantitative information for a biological event in vivo with ultrahigh sensitivity; however, the comparatively lo...
With the increasing growth of multimedia data on the Internet, multimodal image aesthetic assessment has attracted a great deal of attention in the image processing community. However, traditional multimodal methods often have the following two probl...
Multimodal sensors capture and integrate diverse characteristics of a scene to maximize information gain. In optics, this may involve capturing intensity in specific spectra or polarization states to determine factors such as material properties or a...
Hypertrophic cardiomyopathy remains underdiagnosed despite a growing number of effective treatment interventions that can improve care. Multimodality imaging has become integral to diagnosing and managing hypertrophic cardiomyopathy, providing a comp...
Multimodality imaging is a comprehensive strategy to investigate left ventricular hypertrophy (LVH), providing morphologic, functional, and often clinical information to clinicians. Hypertrophic cardiomyopathy (HCM) is defined by an increased LV wall...
Spam detection has been a topic of extensive research; however, there has been limited focus on multimodal spam detection. In this study, we introduce a novel approach for multilingual multimodal spam detection, presenting the Multilingual and Multim...
Stem cell therapy has emerged as a promising approach for treating various retinal diseases, particularly degenerative retinal diseases such as geographic atrophy in age-related macular degeneration (AMD), retinitis pigmentosa (RP), and Stargardt dis...
Cardiac amyloidosis is an underdiagnosed cause of heart failure characterized by extracellular deposition of misfolded proteins. Advances in non-invasive imaging, including echocardiography, cardiac magnetic resonance imaging (CMR), and radionuclide...
Multimodal imaging techniques have the potential to enhance the interpretation of histology by offering additional molecular and structural information beyond that accessible through hematoxylin and eosin (H&E) staining alone. Here, we present a...
A novel multimodal, multiscale imaging system with augmented reality capability were developed and characterized. The system offers 3D color reflectance imaging, 3D fluorescence imaging, and augmented reality in real time. Multiscale fluorescence ima...
Primary cardiac tumors (PCTs) are rare, with benign PCTs being relatively common in approximately 75% of all PCTs. Benign PCTs are usually asymptomatic, and they are found incidentally by imaging. Even if patients present with symptoms, they are usua...
Multimodal image data have found widespread applications in visual-based building façade damage detection in recent years, offering comprehensive inspection of façade surfaces with the assistance of drones and infrared thermography. How...
Breast cancer imaging is central to screening, diagnosis, staging, treatment monitoring, and post-treatment surveillance, but image interpretation remains limited by variable image quality, interobserver variability, false-positive findings and heter...
Olfactory information, crucial for human perception, is often underrepresented compared to visual and textual data. This work explores methods for understanding smell descriptions within a multimodal context, where scent information is conveyed indir...
Multimodal image registration is a fundamental yet challenging task, particularly in remote sensing scenarios involving cross-platform, multi-temporal, and cross-modal data. The primary difficulty arises from the coexistence of large-scale geometric...
Low-light image enhancement (LLIE) is a fundamental yet challenging task due to the presence of noise, loss of detail, and poor contrast in images captured under insufficient lighting conditions. Recent methods often rely solely on pixel-level transf...
The nonlinear radiation distortions (NRD) among multimodal remote sensing images bring enormous challenges to image registration. The traditional feature-based registration methods commonly use the image intensity or gradient information to detect an...
The evaluation of aortic regurgitation (AR) in bicuspid valve (BAV) is still a challenge because of the eccentricity of the jet, which may under/overestimate the regurgitation. The commonly used echocardiography parameters (such as vena contracta, pr...
With the diversification of information retrieval methods, news retrieval tasks have gradually evolved towards multimodal retrieval. Existing methods often encounter issues such as inaccurate alignment and unstable feature matching when handling cros...
Image–text multimodal deep semantic segmentation leverages the fusion and alignment of image and text information and provides more prior knowledge for segmentation tasks. It is worth exploring image–text multimodal semantic segmentation...
Infective endocarditis (IE) represents an important medical challenge, particularly in patients with congenital heart diseases (CHD). Its early and accurate diagnosis is crucial for effective management to improve patient outcomes. Multimodality imag...
Cardiomyopathies are a group of structural and/or functional myocardial disorders which encompasses hypertrophic, dilated, arrhythmogenic, restrictive, and other cardiomyopathies. Multimodality cardiac imaging techniques are the cornerstone of cardio...
Multi-modal image registration is the primary step in integrating information stored in two or more images, which are captured using multiple imaging modalities. In addition to intensity variations and structural differences between images, they may...
Technology-assisted clinical diagnosis has gained tremendous importance in modern day healthcare systems. To this end, multimodal medical image fusion has gained great attention from the research community. There are several fusion algorithms that me...
Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentation, and lesion detection. CNN has great advantages in extracting local...
The term arrhythmogenic cardiomyopathy (ACM) describes a large spectrum of myocardial diseases characterized by progressive fibrotic or fibrofatty replacement, which gives the substrate for the occurrence of ventricular tachyarrhythmias and the devel...
Drug-resistant epilepsy affects nearly one-third of individuals with epilepsy and remains a major cause of neurological morbidity worldwide. Surgical intervention offers a potential cure, but its success critically depends on the precise identificati...
Social media datasets have been widely used in disaster assessment and management. When a disaster occurs, many users post messages in a variety of formats, e.g., image and text, on social media platforms. Useful information could be mined from these...
Photoacoustic microscopy (PAM) is an emerging retinal imaging technique that can provide high spatial resolution and high contrast of chorioretinal vessels. PAM is compatible with optical coherence tomography (OCT) and fluorescence imaging, allowing...
Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sud...
Marfan syndrome (MFS) is a genetic disorder affecting connective tissue, often leading to cardiovascular complications such as aortic aneurysms and mitral valve prolapse. Cardiovascular multimodality imaging plays a crucial role in the diagnosis, mon...
Magnetic resonance (MR) imaging is widely used in the clinical field due to its non-invasiveness, but the long scanning time is still a bottleneck for its popularization. Using the complementary information between multi-modal imaging to accelerate i...
Background/Objectives: To investigate the role of multimodal imaging, including ultra-widefield fundus autofluorescence (UWFAF), in diagnosing and monitoring syphilitic chorioretinitis, focusing on the detection of placoid appearance and white dots/s...
In this study, we leverage advancements in large language models (LLMs) for fine-grained food image classification. We achieve this by integrating textual features extracted from images using an LLM into a multimodal learning framework. Specifically,...
Matching remotely sensed multimodal images is a crucial process that poses significant challenges due to nonlinear radiometric differences and substantial image noise. To overcome these difficulties, this study presents a novel and practical template...
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