This paper presents a multichannel deep-learning method for detecting lung diseases using chest X-ray images. Using EfficientNetB0 through EfficientNetB7 pretrained models, the methodology offers improved performance in classifying COVID-19, viral pneumonia, and normal chest Xrays.

This study aims to optimize the downgrading of BI-RADS class 4a nodules by combining various sectional elastography techniques with age.

Pulmonary sclerosing haemangioma (PSH) is a relatively uncommon benign neoplasm that is often asymptomatic and predominantly affects young and middle-aged females. PSH often appears as a single nodule, whereas multiple lesions with a cavity are relatively rare and easily misdiagnosed.

This research assesses HRNet and ResNet architectures for their precision in localizing hand acupoints on 2D images, which is integral to automated acupuncture therapy.

This study aimed to verify whether the Liver-to-portal Ratio (LPR) can assess the adequacy of the Hepatobiliary Phase (HBP) for patients with different liver functions.

The most common primary malignant brain tumor is glioblastoma. Glioblastoma Multiforme (GBM) diagnosis is difficult. However, image segmentation and registration methods may simplify and automate Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scan analysis. Medical practitioners and researchers can better identify and characterize glioblastoma tumors using this technology. Many segmentation and registration approaches have been proposed recently. Note that these approaches are not fully compiled. This review efficiently and critically evaluates the state-of-the-art segmentation and registration techniques for MRI and CT GBM images, providing researchers, medical professionals, and students with a wealth of knowledge to advance GBM imaging and inform decision-making. GBM's origins and development have been examined, along with medical imaging methods used to diagnose tumors. Image segmentation and registration were examined, showing their importance in this difficult task. Frequently encountered glioblastoma segmentation and registration issues were examined. Based on these theoretical foundations, recent image segmentation and registration advances were critically analyzed. Additionally, evaluation measures for analytical efforts were thoroughly reviewed.

Magnetic Resonance Imaging (MRI) data acquisition includes several sequences that might be optimized to reduce the scan time.

Eosinophilic gastroenteritis (EGE) is a rare immune-mediated chronic inflammatory disorder, which is classified into 3 types according to the affected gastric wall layer. The serosal-type EGE is the least common type. Gastric oral contrast-enhanced ultrasonography (OCEUS) may show some specific changes in the serosal-type EGE. Herein, we reported OCEUS findings in a serosal-type EGE case.

Dural sinus arteriovenous malformation is an uncommon intracranial vascular malformation. The affected cases may suffer from severe neurological injury. Prenatal ultrasound has been used to diagnose fetal intracranial vascular abnormality, but prenatal three-dimensional (3D) ultrasound presents a very rare anomaly; an arteriovenous malformation of the dural sinus has not been reported.

Guizhi Shaoyao Zhimu Decoction can be used in the treatment of rheumatoid arthritis, but there is scarce literature on using ultrasound combined with electrophysiology to evaluate the efficacy of this traditional Chinese medicine.

Multimodal medical image fusion techniques play an important role in clinical diagnosis and treatment planning. The process of combining multimodal images involves several challenges depending on the type of modality, transformation techniques, and mapping of structural and metabolic information.

In this study, we harnessed three cutting-edge algorithms' capabilities to refine the elbow fracture prediction process through X-ray image analysis. Employing the YOLOv8 (You only look once) algorithm, we first identified Regions of Interest (ROI) within the X-ray images, significantly augmenting fracture prediction accuracy.

Three-dimensional (3D) whole-heart magnetic resonance imaging (MRI) is an excellent tool to check the heart anatomy of patients with congenital and acquired heart disease. However, most 3D whole-heart MRI acquisitions take a long time to perform, and the sequence used is susceptible to banding artifacts.

The use of Magnetic Resonance Imaging (MRI) and radiomics improves the management of Prostate Cancer (PCa) and helps in differentiating between clinically insignificant and significant PCa. This study has explored the diagnostic value of radiomic analysis based on functional parameter maps from monoexponential and diffusion kurtosis models in MRI for differentiating between clinically insignificant and significant PCa.

Kikuchi-Fujimoto Disease (KFD) is a rare condition, distinguished by its hallmark presentation of regional lymphadenopathy in young adult females. While initially observed to exclusively affect cervical lymph nodes in females under 40 years old, KFD is now known to impact individuals of any age or gender and manifest with adenopathy in various anatomical sites. Nonspecific imaging findings for KFD include enlarged lymph nodes, often exhibiting abnormal morphology.

This study aimed to establish a model based on Multi-detector Computed Tomography (MDCT), F-fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (F-FDG PET/CT), and clinical features for predicting different growth patterns of preoperative Invasive Adenocarcinoma (IAC).

The maxillary sinuses are air-filled cavities which vary in size and shape. Sinus radiography has been widely used in the determination of the gender of the individual, especially in forensic investigation for human identification and sexing of individuals. The advanced radiographic techniques like cone beam computed tomography (CBCT), especially the axial and coronal sections, have been considered as a subtle concept in forensic odontology.

Applications of artificial intelligence (AI) in medical ultrasound have rapidly grown in recent years. Therefore, it is necessary to identify and visualize global research trends and hotspots of AI in medical ultrasound to provide guidance for further exploitation.

Immune checkpoint inhibitor-related pneumonitis (ICI-P) is a fatal adverse event of immunotherapy. However, there is a lack of methods to identify patients who have a high risk of developing ICI-P in immunotherapy.

Patients with malignant tumors often develop bone metastases. SPECT bone scintigraphy is an effective tool for surveying bone metastases due to its high sensitivity, low-cost equipment, and radiopharmaceutical. However, the low spatial resolution of SPECT scans significantly hinders manual analysis by nuclear medicine physicians. Deep learning, a promising technique for automated image analysis, can extract hierarchal patterns from images without human intervention.

Controversies still exist regarding the mechanism formation of the blend sign, defined as hypodensity and hyperdensity regions, in Intracerebral Hemorrhage (ICH), and which region associated with bleeding remains unknown. Spot sign is an independent predictor of hematoma expansion (HE) and indicates persistent bleeding focus in the hematoma. Here, we sought to establish the relationship between the spot sign and the blend sign to gain insights into the formation of the blend sign.