Background: Upper respiratory tract infection is a common disease of the respiratory system. Its incidence is very high, and it can even cause pandemics. Infrared thermal imaging (IRTI) can provide an objective and quantifiable reference for the visual diagnosis of people with acute respiratory tract infection, and it can function as an effective indicator of clinical diagnosis.
View Article and Find Full Text PDFBackground And Objective: Infrared thermal imaging (IRTI) is a new technique for detecting deep vein thrombosis (DVT) based on DVT's infrared presentation and distribution characteristics (PDCs). A method that is singularly sensitive to DVT is needed. They, therefore, enrolled 157 subjects with suspected lower extremity DVT in a double-blind, controlled clinical trial using IRTI, and Doppler compression ultrasonography (CPUS) to verify the clinical value of IRTI.
View Article and Find Full Text PDFPurpose: The authors aimed to determine the effectiveness of infrared thermal imaging (IRTI) as a novel, noninvasive technique in adjunctive diagnostic screening for lower limb deep venous thrombosis (DVT).
Methods: The authors used an infrared thermal imaging sensor to examine the lower limbs of 64 DVT patients and 64 healthy volunteers. The DVT patients had been definitively diagnosed with either Doppler vascular compression ultrasonography or angiography.
Purpose: Early detection of deep vein thrombosis (DVT) is critical to prevent clinical pulmonary thromboembolism. However, most conventional methods for diagnosing DVT are functionally limited and complicated. The aim of this study was to evaluate the value of infrared-thermal-imaging (IRTI), a novel imaging detection or screening technique, in diagnosis of DVT in animal models.
View Article and Find Full Text PDFBackground And Aims: Because there is no complete three-dimensional (3D) hybrid detector integrated PET+MRI internationally, this study aims to investigate a registration approach for a two-dimensional (2D) hybrid based on characteristic localization to achieve a 3D fusion from the images of PET and MRI as a whole.
Methods: A cubic-oriented scheme of "9-point and 3-plane" for a coregistration design was verified to be geometrically practical. Through 3D reconstruction and virtual dissection, human internal feature points were sorted to combine with preselected external feature points for matching process.