The ultrasound fusion imaging (UFI) system is a new promising imaging modality that combines live ultrasound investigations with preregistered CT, MRI, or PET images. In this study, we want to present our initial experience with the new method that combines the transcranial color-coded sonography (TCCS) in different insonation planes and the 3T-weighted MRI cerebral images. The study validates the diagnostic capabilities of the system to detect different normal cerebral structures in healthy volunteers. In the present paper, we also discuss the advantages of US fusion imaging technology and its clinical applications in Neurology.

Download full-text PDF

Source
http://dx.doi.org/10.3897/folmed.64.e64271DOI Listing

Publication Analysis

Top Keywords

fusion imaging
12
ultrasound fusion
8
images study
8
imaging
4
imaging system
4
system neurology
4
neurology practice
4
practice ultrasound
4
imaging ufi
4
ufi system
4

Similar Publications

Autism spectrum disorder (ASD) is a neurologic disorder considered to cause discrepancies in physical activities, social skills, and cognition. There is no specific medicine for treating this disorder; early intervention is critical to improving brain function. Additionally, the lack of a clinical test for detecting ASD makes diagnosis challenging.

View Article and Find Full Text PDF

GPS/VIO integrated navigation system based on factor graph and fuzzy logic.

Sci Rep

December 2024

Department of Electrical Engineering, Iran University of Science and Technology, Tehran, 16846-13114, Iran.

In today's technologically advanced landscape, precision in navigation and positioning holds paramount importance across various applications, from robotics to autonomous vehicles. A common predicament in location-based systems is the reliance on Global Positioning System (GPS) signals, which may exhibit diminished accuracy and reliability under certain conditions. Moreover, when integrated with the Inertial Navigation System (INS), the GPS/INS system could not provide a long-term solution for outage problems due to its accumulated errors.

View Article and Find Full Text PDF

Multi-modal medical images are important in tumor lesion detection. However, the existing detection models only use single-modal to detect lesions, a multi-modal semantic correlation is not enough to consider and lacks ability to express the shape, size, and contrast degree features of lesions. A Cross Modal YOLOv5 model (CMYOLOv5) is proposed.

View Article and Find Full Text PDF

Multimodal Deep Learning Fusing Clinical and Radiomics Scores for Prediction of Early-Stage Lung Adenocarcinoma Lymph Node Metastasis.

Acad Radiol

December 2024

School of Public Health, Jiangxi Medical College, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.); Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.). Electronic address:

Rationale And Objectives: To develop and validate a multimodal deep learning (DL) model based on computed tomography (CT) images and clinical knowledge to predict lymph node metastasis (LNM) in early lung adenocarcinoma.

Materials And Methods: A total of 724 pathologically confirmed early invasive lung adenocarcinoma patients were retrospectively included from two centers. Clinical and CT semantic features of the patients were collected, and 3D radiomics features were extracted from nonenhanced CT images.

View Article and Find Full Text PDF

Objectives: To determine how many cores should be collected per region of interest in magnetic resonance imaging (MRI)-guided fusion prostate biopsy. MRI-guided targeted prostate biopsy has led to improved detection of clinically significant prostate cancer (csPC); however, data is limited regarding the optimal number of biopsy cores that should be taken. An ideal number of cores maximizes clinically significant cancer detection while minimizing cost, discomfort, and procedure time.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!