Since 1981, we have been able to modify the mathematical patterns of projection geometry to reshape the skull in craniofacial surgery. Unlike burring, morcellization, rotation, and plate switching, this technique actually changes the shape of individual sections of the skull by changing their radius of curvature. The technique is an adaptation of the principles used by engineers to build complex structures such as ships' hulls, airfoils, and domes. The result is a rigid form of the desired shape that becomes permanent with healing. This has several advantages: 1. An increase in the level of safety of craniofacial procedures for remodeling the skull. This is so because there is no need to dissect normal areas as in the standard plate-switching techniques. 2. Decreased operating room time. 3. An increased range of surgical manipulations. No longer is the surgeon limited to the shape of the material present. 4. Relief of edge pressure on the frontal lobes during scalp closure. 5. Creation of a solid bony form over which the pericranial scalp flap can be draped to form new layers of bone.
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http://dx.doi.org/10.1097/00006534-198902000-00002 | DOI Listing |
J Neural Eng
January 2025
Weldon School of Biomedical Engineering, Purdue University, 723 W. Michigan St., Indianapolis, Indiana, 46202, UNITED STATES.
Objective: Direct electrical neurostimulation using continuous sinusoidal low frequency alternating currents (LFAC) is an emerging modality for neuromodulation. As opposed to the traditional rectangular pulse stimulation, there is limited background on the characteristics of peripheral nerves responses to sinusoidal LFAC stimulation; especially within the low frequency range (<50Hz). In this study, we demonstrate LFAC activation as a means to activate motor nerves by direct bipolar nerve stimulation via cuff electrodes, and characterize the factors of activation.
View Article and Find Full Text PDFEJNMMI Phys
January 2025
Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden.
Background: System calibration is essential for accurate SPECT/CT dosimetry. However, count losses due to dead time and pulse pileup may cause calibration errors, in particular for I, where high count rates may be encountered. Calibration at low count rates should also be avoided to minimise detrimental effects from e.
View Article and Find Full Text PDFMed Image Anal
January 2025
Department of Engineering Science, University of Oxford, Oxford, UK.
Cardiac digital twins (CDTs) offer personalized in-silico cardiac representations for the inference of multi-scale properties tied to cardiac mechanisms. The creation of CDTs requires precise information about the electrode position on the torso, especially for the personalized electrocardiogram (ECG) calibration. However, current studies commonly rely on additional acquisition of torso imaging and manual/semi-automatic methods for ECG electrode localization.
View Article and Find Full Text PDFMed Image Anal
January 2025
Department of Applied Mathematics, Technical Medical Centre, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands.
The orientation of a blood vessel as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation, labeling, and visualization. Blood vessels appear at multiple scales and levels of tortuosity, and determining the exact orientation of a vessel is a challenging problem. Recent works have used 3D convolutional neural networks (CNNs) for this purpose, but CNNs are sensitive to variations in vessel size and orientation.
View Article and Find Full Text PDFLight Sci Appl
January 2025
School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN, 47907, USA.
Multi-photon polymerization is a well-established, yet actively developing, additive manufacturing technique for 3D printing on the micro/nanoscale. Like all additive manufacturing techniques, determining the process parameters necessary to achieve dimensional accuracy for a structure 3D printed using this method is not always straightforward and can require time-consuming experimentation. In this work, an active machine learning based framework is presented for determining optimal process parameters for the recently developed, high-speed, layer-by-layer continuous projection 3D printing process.
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