Fully automated segmentation of brain and scalp blood vessels on multi-parametric magnetic resonance imaging using multi-view cascaded networks.

Background And Objective: Neurosurgical navigation is a critical element of brain surgery, and accurate segmentation of brain and scalp blood vessels is crucial for surgical planning and treatment. However, conventional methods for segmenting blood vessels based on statistical or thresholding techniques have limitations. In recent years, deep learning-based methods have emerged as a promising solution for blood vessel segmentation, but the segmentation of small blood vessels and scalp blood vessels remains challenging.

Research progress of nitroxide radical-based MRI contrast agents: from structure design to application.

Magnetic resonance imaging (MRI) remains a cornerstone of diagnostic imaging, offering unparalleled insights into anatomical structures and pathological conditions. Gadolinium-based contrast agents have long been the standard in MRI enhancement, yet concerns over nephrogenic systemic fibrosis have spurred interest in metal-free alternatives. Nitroxide radical-based MRI contrast agents (NO-CAs) have emerged as promising candidates, leveraging their biocompatibility and imaging capabilities.

A classic prescription alleviates inflammation in CUMS model mice via modulating MYDGF/MAP4K4/NF-κB signaling pathway, verified through UPLC-HRMS and proteomics analysis.

Background: Xiaoyaosan (XYS), a renowned classical traditional Chinese medicinal formula utilized in addressing major depressive disorder (MDD), has garnered significant acclaim for its remarkable efficacy in clinical application. The onset of major depressive disorder (MDD) often correlates with chronic unpredictable mild stress (CUMS), a pivotal instigating factor in its development.: This study aims to clarify the potential anti-inflammatory mechanisms of XYS in treating CUMS model mice.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System.

Objectives: Freehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference.

A two-stage deep-learning framework for CT denoising based on a clinically structure-unaligned paired data set.

Background: In low-dose computed tomography (LDCT) lung cancer screening, soft tissue is hardly appreciable due to high noise levels. While deep learning-based LDCT denoising methods have shown promise, they typically rely on structurally aligned synthesized paired data, which lack consideration of the clinical reality that there are no aligned LDCT and normal-dose CT (NDCT) images available. This study introduces an LDCT denoising method using clinically structure-unaligned but paired data sets (LDCT and NDCT scans from the same patients) to improve lesion detection during LDCT lung cancer screening.

MLNAN: Multi-level noise-aware network for low-dose CT imaging implemented with constrained cycle Wasserstein generative adversarial networks.

Low-dose CT techniques attempt to minimize the radiation exposure of patients by estimating the high-resolution normal-dose CT images to reduce the risk of radiation-induced cancer. In recent years, many deep learning methods have been proposed to solve this problem by building a mapping function between low-dose CT images and their high-dose counterparts. However, most of these methods ignore the effect of different radiation doses on the final CT images, which results in large differences in the intensity of the noise observable in CT images.

Automatic brain structure segmentation for F-fluorodeoxyglucose positron emission tomography/magnetic resonance images via deep learning.

Background: Brain structure segmentation is of great value in diagnosing brain disorders, allowing radiologists to quickly acquire regions of interest and assist in subsequent analyses, diagnoses and treatment. Current brain structure segmentation methods are usually applied to magnetic resonance (MR) images, which provide higher soft tissue contrast and better spatial resolution. However, fewer segmentation methods are conducted on a positron emission tomography/magnetic resonance imaging (PET/MRI) system that combines functional and structural information to improve analysis accuracy.

[Clinical characteristics and etiology of temporomandibular joint herniation into external ear canal].

To summarize the cases of temporomandibular joint herniation into external auditory canal found and treated in our hospital, to improve the understanding of oral and maxillofacial diseases and otological diseases, and to explore the potential long-term effects of local radiotherapy on temporomandibular joint function. Analyzed the causes of temporomandibular joint herniation into external auditory canal comprehensively through combining history, clinical manifestations and imaging examination. All otoscope results showed soft tissue mass in the deep anterior wall of the external auditory canal.

The arch bridge sign: a newly described CT feature of the coronavirus disease-19 (COVID-19) pneumonia.

Background: To investigate the distribution of CT features and also to introduce a novel described CT feature of coronavirus disease-19 (COVID-19) pneumonia.

Methods: A series of radiologic signs in 11 COVID-19 patients were summarized and made morphometric analysis.

Results: A special sign termed as "the arch bridge sign" owing to its morphological mimicking an arch bridge was firstly introduced.

Computed Tomographic Imaging of 3 Patients With Coronavirus Disease 2019 Pneumonia With Negative Virus Real-time Reverse-Transcription Polymerase Chain Reaction Test.

We reported computed tomographic (CT) imaging findings of 3 patients with coronavirus disease 2019 (COVID-19) pneumonia with initially negative results before CT examination and finally confirmed positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by real-time reverse-transcription polymerase chain reaction assay.

BRD4 blockage alleviates pathological cardiac hypertrophy through the suppression of fibrosis and inflammation via reducing ROS generation.

Hypertension is an essential regulator of cardiac injury and remodeling. However, the pathogenesis that contributes to cardiac hypertrophy remains to be fully explored. BRD4, as a bromodomain and extra-terminal (BET) family member, plays an important role in critical biological processes.