Catching Physiological Noise: Comparison of DRIFTER in Image and k-Space Arno Solin, Simo Särkkä, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, and Fa-Hsuan Lin Department of Biomedical Engineering and Computational Science, Aalto University, Espoo, Finland, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, Advanced Magnetic Imaging Cen...

Department of Chemistry, Duke University, Durham, NC 27708, USA. Department of Physics, Duke University, Durham, NC 27708, USA. Department of Mechanical Engineering andMaterials Science, DukeUniversity, Durham,NC27708, USA. Departments of Radiology and Biomedical Engineering, Vanderbilt University, Institute of Imaging Science, Nashville, TN 37232, USA. Departments of Radiology and Biomedical E...

Biomedical computing applications often follow a computational pipeline: experimental data or image acquisition, mathematical modeling, geometric modeling (segmentation, mesh generation), material modeling, numerical approximation (finite element analysis, linear solvers, nonlinear optimization), visualization (of the geometric model, material model, and solutions), and validation. An important...

Many computer vision algorithms have been successfully adapted and applied to biomedical imaging applications. However, biomedical computer vision is far beyond being only an application field. Indeed, it is a wide field with huge potential for developing novel concepts and algorithms and can be seen as a driving force for computer vision research. To emphasize this view of biomedical computer ...

Increasingly wider availability of biomedical imaging modalities, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), ultrasonic imaging, positron emission tomography (PET), single-photon emission computed tomography (SPECT), and optical imaging, have led to significant progresses in both biomedical research and clinical practice. Advancements in imaging technology and ima...

Emerging materials and methods in biomedical imaging and biophotonics are improving patient outcomes. More specifi cally, the utilization of biomedical diagnostics and therapeutic advances in methods such as magnetic resonance imaging (MRI), computed tomography (CT) imaging, photoacoustic tomography, photothermal optical coherence tomography, and targeted photothermal therapy (PTT) have been sh...

An Iterative Self-Navigation Approach to Improve Image Quality in Subjects with Irregular Breathing in Whole Heart Coronary MRA. Giulia Ginami, Gabriele Bonanno, Juerg Schwitter, Matthias Stuber, and Davide Piccini Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, Department of Radiology, University hospital (CHUV) and University of Lausanne (Unil), Lausanne, Switzerland, Department ...

magnetic nanoparticles are the good choice for using in mri as the contrast agent. iron oxide particles such as magnetite (fe3o4) or its oxidized form maghemite (γ-fe2o3) are the most commonly employed in biomedical applications. in this study, we synthesized and optimized the preparation of chitosan manganese-ferrite nanoparticles (cmn-fe nps) and evaluated its ability for the mice macrophage ...

Noble metal clusters have unique photophysical properties, especially as a new class of materials for multiphoton biomedical imaging.