A surface matching technique has been developed to register multiple imaging scans of the brain in three dimensions, with accuracy on the order of the image pixel sizes. Anatomic information visualized in X-ray CT and magnetic resonance images may be integrated with each other and with functional information from positron emission tomography. Anatomical structures and other volumes of interest may be mapped from one scan to another, and corresponding sections through multiple scans may be directly compared. This capability provides a novel quantitative method to address the fundamental problem of relating structure to function in the brain. Applications include basic and clinical problems in the neurosciences and delivery and assessment of brain tumor therapy.
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http://dx.doi.org/10.1097/00004728-198901000-00004 | DOI Listing |
J Vis Exp
January 2025
School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine;
The therapeutic effectiveness of acupuncture relies on both safety and stability, making these factors essential in acupuncture manipulation research. However, manual manipulation introduces unavoidable inaccuracies, which can impact the reliability of research findings. To address this challenge, a unique lifting and thrusting manipulation control cannula was designed in this study, offering flexible adjustment of movement amplitude.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Hangzhou, 310006, China.
Objectives: To evaluate recent advances in the automatic multimodal registration of cone-beam computed tomography (CBCT) and intraoral scans (IOS) and their clinical significance in dentistry.
Methods: A comprehensive literature search was conducted in October 2024 across the PubMed, Web of Science, and IEEE Xplore databases, including studies that were published in the past decade. The inclusion criteria were as follows: English-language studies, randomized and nonrandomized controlled trials, cohort studies, case-control studies, cross-sectional studies, and retrospective studies.
J Transl Int Med
February 2024
Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University; NHC Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Peking University; Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China.
Background And Objective: Hemodynamic changes that lead to increased blood pressure represent the main drivers of organ damage in hypertension. Prolonged increases to blood pressure can lead to vascular remodeling, which also affects vascular hemodynamics during the pathogenesis of hypertension. Exercise is beneficial for relieving hypertension, however the mechanistic link between exercise training and how it influences hemodynamics in the context of hypertension is not well understood.
View Article and Find Full Text PDFDeep learning has become an attractive tool for addressing the limitations of traditional digital image correlation (DIC). However, extending learning-based DIC methods to three-dimensional (3D-DIC) measurements is challenging due to the limited displacement estimation range, which cannot handle the large displacements caused by stereo-matching disparities. Besides, most of the existing learning-based DIC architectures lack prior information to guide displacement estimation, resulting in insufficient accuracy.
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