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Preliminary Evidence for Perturbation-Based tACS-EEG Biomarkers of Gamma Activity in Alzheimer's Disease.
Int J Geriatr Psychiatry
January 2025
Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Background: Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30-90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal "Perturbation-based" transcranial Alternating Current Stimulation-Electroencephalography (tACS)-EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype.
View Article and Find Full Text PDFComparative analysis of imaging and pathological features in diagnosis of endometrial carcinosarcoma based on multimodal MRI.
Arch Gynecol Obstet
January 2025
Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong Road, Nanning, 530021, Guangxi, China.
Purpose: This case report aims to present a rare case of endometrial carcinosarcoma, a highly malignant tumor with a poor prognosis. The primary objective is to describe this unique case's clinical presentation, multimodal magnetic resonance imaging (MRI) features, typical histopathological characteristics and surgical treatment.
Methods: A detailed analysis of the patient's medical history, preoperative imaging evaluation, and treatment approach was conducted.
Predictors of Peripheral Retinal Non-Perfusion in Clinically Significant Diabetic Macular Edema.
J Clin Med
December 2024
Lions Eye Institute, Perth, WA 6009, Australia.
Diabetic macular edema (DME) is a significant cause of vision loss. The development of peripheral non-perfusion (PNP) might be associated with the natural course, severity, and treatment of DME. The present study seeks to understand the predictive power of central macular changes and clinico-demographic features for PNP in patients with clinically significant DME.
View Article and Find Full Text PDFA Comparison Study of Person Identification Using IR Array Sensors and LiDAR.
Sensors (Basel)
January 2025
Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
Person identification is a critical task in applications such as security and surveillance, requiring reliable systems that perform robustly under diverse conditions. This study evaluates the Vision Transformer (ViT) and ResNet34 models across three modalities-RGB, thermal, and depth-using datasets collected with infrared array sensors and LiDAR sensors in controlled scenarios and varying resolutions (16 × 12 to 640 × 480) to explore their effectiveness in person identification. Preprocessing techniques, including YOLO-based cropping, were employed to improve subject isolation.
View Article and Find Full Text PDFPrior-FOVNet: A Multimodal Deep Learning Framework for Megavoltage Computed Tomography Truncation Artifact Correction and Field-of-View Extension.
Sensors (Basel)
December 2024
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Megavoltage computed tomography (MVCT) plays a crucial role in patient positioning and dose reconstruction during tomotherapy. However, due to the limited scan field of view (sFOV), the entire cross-section of certain patients may not be fully covered, resulting in projection data truncation. Truncation artifacts in MVCT can compromise registration accuracy with the planned kilovoltage computed tomography (KVCT) and hinder subsequent MVCT-based adaptive planning.
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