The synthesis of sMoSe₂–ICG NSs for highly efficient tumor photoacoustic imaging guided photothermal therapy.

Recent advancements in large language models (LLMs) have demonstrated extraordinary comprehension capabilities with remarkable breakthroughs on various vision-language tasks. However, the application of LLMs generating reliable medical diagnostic reports remains early stages. Currently, typically feature a passive interaction model where doctors respond to patient queries little or no involvement analyzing images. In contrast, some ChatBots simply predefined based visual inputs, lacking...

The relationship between theoretical descriptions of imaging performance (Fourier-based) and the real human observers was investigated for detection tasks in multi-slice CT. detectability index Fisher-Hotelling model observer non-prewhitening (with without internal noise eye filter) computed using: 1) measured modulation transfer function (MTF) noise-power spectrum (NPS) CT; 2) a Fourier description task. Based upon CT images patients with added simulated lesions, assessed via an study terms...

With the rapid advances of light source technology, A-line imaging rate swept-source optical coherence tomography (SS-OCT) has experienced a great increase in past three decades. The bandwidths data acquisition, transfer, and storage, which can easily reach several hundred megabytes per second, have now been considered major bottlenecks for modern SS-OCT system design. To address these issues, various compression schemes previously proposed. However, most current methods focus on enhancing...

Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis treatment of CAD. Constrained by Nyquist theorem, dense sampling in IVOCT attains resolving power to delineate cellular structures/features. There trade-off between spatial resolution fast scanning rate coronary imaging. In this paper, we propose viable spectral-spatial...

Abstract American football games attract significant worldwide attention every year. Identifying players from videos in each play is also essential for the indexing of player participation. Processing game video presents great challenges such as crowded settings, distorted objects, and imbalanced data identifying players, especially jersey numbers. In this work, we propose a deep learning-based tracking system to automatically track index their participation per games. It two-stage network...

ABSTRACT We create a series of detailed computerized phantoms to esti mate patient organ and effective dose in pediatric CT investigate techniques for efficiently creating patient-specific based on imaging data. The initial anatomy each phantom was previously developed manual segmentation Each extended include more morphing an existing adult our laboratory match the framework (based segmentation) defined target model. By template data LDDMM framework, it possible specific with many...

Optical coherence tomography (OCT) has stimulated a wide range of medical image-based diagnosis and treatment in fields such as cardiology ophthalmology. Such applications can be further facilitated by deep learning-based super-resolution technology, which improves the capability resolving morphological structures. However, existing method only focuses on spatial distribution disregards frequency fidelity image reconstruction, leading to bias. To overcome this limitation, we propose...

Histopathological analysis is crucial in artery characterization for coronary disease (CAD). However, histology requires an invasive and time-consuming process. In this paper, we propose to generate virtual staining using Optical Coherence Tomography (OCT) images enable real-time histological visualization. We develop a deep learning network, namely Coronary-GAN, transfer OCT images. With special consideration on the structural constraints images, our method achieves better image generation...

Optical coherence tomography (OCT) has become increasingly essential in assisting the treatment of coronary artery disease (CAD). Image-guided solutions such as Percutaneous Coronary Intervention (PCI) are extensively used during CAD. However, unidentified calcified regions within a narrowed could impair outcome PCI. Prior to treatments, object detection is paramount automatically procure accurate readings on location and thickness calcifications artery. Deep learning-based methods have been...

A model for the distribution function P(\ensuremath{\sigma},\ensuremath{\eta}) axial and eccentric orientational order parameters \ensuremath{\sigma} \ensuremath{\eta} is proposed a system of quadrupoles which represents situation in solid ${\mathrm{H}}_{2}$ ${\mathrm{D}}_{2}$. It based on plausible approximation to exact one-particle density matrix J=1 molecules randomly distributed (J${=1)}_{X}$(J${=0)}_{(1\mathrm{\ensuremath{-}}X)}$ solid, where X molar concentration component. The...

Gastric motility disorders are caused by abnormal muscle contractions which may impede the digestive process. Traditional approaches for evaluating human gastric have limitations, including discomfort, use of sedation, risk radiation exposure, and confusion in interpretation. Magnetically controlled capsule endoscopy (MCCE) provides a new way to evaluate with advantages comfort, safety, no anesthesia. In this paper, we develop deep learning algorithms detect waves captured MCCE. We...

Cumulative screen exposure has been increased due to the explosion of digital technology ownership in past decade for all people, including children who face related risks such as obesity, eye problems, and disrupted sleep. Screen is linked physical mental health among both adults. Current methods assessment have their limitations, mostly prospective objectiveness, robustness, invasiveness. In this paper, we propose a novel method measure time using wearable sensor computer vision...

The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for assessing gastrointestinal disorders due to its advantages. However, current assignments of MCCE rely on manual controlling and gastric landmarks, which are prone omissions. We improve the scanning protocol in human using both automatic methods. design a quantitative coverage ratio measure process within gastric. proposed capable guiding Moreover, we deep reinforcement learning (DRL) controller automatically...

SignificanceThere is a significant need for the generation of virtual histological information from coronary optical coherence tomography (OCT) images to better guide treatment artery disease (CAD). However, existing methods either require large pixel-wise paired training dataset or have limited capability map pathological regions.AimThe aim this work generate OCT images, without while capable providing patterns.ApproachWe design structurally constrained, pathology-aware, transformer...

Being able to accurately monitor the screen exposure of young children is important for research on phenomena linked use such as childhood obesity, physical activity, and social interaction. Most existing studies rely upon self-report or manual measures from bulky wearable sensors, thus lacking efficiency accuracy in capturing quantitative data. In this work, we developed a novel sensor informatics framework that utilizes egocentric images sensor, termed time tracker (STT), vision language...

Efficient patient-doctor interaction is among the key factors for a successful disease diagnosis. During conversation, doctor could query complementary diagnostic information, such as patient's symptoms, previous surgery, and other related information that goes beyond medical evidence data (test results) to enhance However, this procedure usually time-consuming less-efficient, which can be potentially optimized through computer-assisted systems. As such, we propose dialogue system automate...

Magnetically controlled capsule endoscope (MCCE) is an emerging tool for the diagnosis of gastric diseases with advantages comfort, safety, and no anesthesia. In this paper, we develop algorithms to detect measure human peristalsis (contraction wave) using video sequences acquired by MCCE. We a spatial-temporal deep learning algorithm contraction waves periods. The quality MCCE prone camera motion. design motion detector (CMD) process sequences, mitigating movement during examination. To...

The change in the transmitted signal amplitude of longitudinal sound with temperature is studied ${\mathrm{D}}_{2}$ upon thermally cycling a crystal, grown hcp phase, between 1.5 K and melting point, before after crossing martensitic hcp-fcc transition. These other experiments lead to conclusion that an intermediate close-packed structure progressively stabilized at expense cubic phase above transition until point. This contrary conclusions from previous also striking contrast behavior...