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RESULTS The proposed method was applied to ten test subjects for the estimation of the respiratory motion field. The quantitative analysis resulted in a mean target registration error of 1.5 (0.8) mm and an average symmetric surface distance of 1.4 (0.6) mm. CONCLUSIONS The proposed method shows remarkable advantages over traditional methods in preserving local motion details and reducing the estimation error in the ROI. These results also provide a benchmark for lung respiratory motion modelling in the literature.PURPOSE An intraoperative real-time respiratory tumor motion prediction system with magnetic tracking technology is presented. Based on respiratory movements in different body regions, it provides patient and single/multiple tumor-specific prediction that facilitates the guiding of treatments. Selleckchem YM201636 METHODS A custom-built phantom patient model replicates the respiratory cycles similar to a human body, while the custom-built sensor holder concept is applied on the patient's surface to find optimum sensor number and their best possible placement locations to use in real-time surgical navigation and motion prediction of internal tumors. Automatic marker localization applied to patient's 4D-CT data, feature selection and Gaussian process regression algorithms enable off-line prediction in the preoperative phase to increase the accuracy of real-time prediction. RESULTS Two evaluation methods with three different registration patterns (at fully/half inhaled and fully exhaled positions) were used quantitatively at all internal target positions in phantom The statical method evaluates the accuracy by stopping simulated breathing and dynamic with continued breathing patterns. The overall root mean square error (RMS) for both methods was between [Formula see text] and [Formula see text]. The overall registration RMS error was [Formula see text]. The best prediction errors were observed by registrations at half inhaled positions with minimum [Formula see text], maximum [Formula see text]. The resulting accuracy satisfies most radiotherapy treatments or surgeries, e.g., for lung, liver, prostate and spine. CONCLUSION The built system is proposed to predict respiratory motions of internal structures in the body while the patient is breathing freely during treatment. The custom-built sensor holders are compatible with magnetic tracking. Our presented approach reduces known technological and human limitations of commonly used methods for physicians and patients.PURPOSE A better understanding of photometry in laparoscopic images can increase the reliability of computer-assisted surgery applications. Photometry requires modelling illumination, tissue reflectance and camera response. There exists a large variety of light models, but no systematic and reproducible evaluation. We present a review of light models in laparoscopic surgery, a unified calibration approach, an evaluation methodology, and a practical use of photometry. METHOD We use images of a calibration checkerboard to calibrate the light models. We then use these models in a proposed dense stereo algorithm exploiting the shading and simultaneously extracting the tissue albedo, which we call dense shading stereo. The approach works with a broad range of light models, giving us a way to test their respective merits. RESULTS We show that overly complex light models are usually not needed and that the light source position must be calibrated. We also show that dense shading stereo outperforms existing methods, in terms of both geometric and photometric errors, and achieves sub-millimeter accuracy. CONCLUSION This work demonstrates the importance of careful light modelling and calibration for computer-assisted surgical applications. It gives guidelines on choosing the best performing light model.Neurological disorders such as Alzheimer's disease (AD), Lewy body dementia (LBD), frontotemporal dementia (FTD), and vascular dementia (VCID) have no disease-modifying treatments to date and now constitute a dementia crisis that affects 5 million in the USA and over 50 million worldwide. The most common pathological hallmark of these age-related neurodegenerative diseases is the accumulation of specific proteins, including amyloid beta (Aβ), tau, α-synuclein (α-syn), TAR DNA-binding protein 43 (TDP43), and repeat-associated non-ATG (RAN) peptides, in the intra- and extracellular spaces of selected brain regions. Whereas it remains controversial whether these accumulations are pathogenic or merely a byproduct of disease, the majority of therapeutic research has focused on clearing protein aggregates. Immunotherapies have garnered particular attention for their ability to target specific protein strains and conformations as well as promote clearance. Immunotherapies can also be neuroprotective by neutralizing extracellular protein aggregates, they reduce spread, synaptic damage, and neuroinflammation. This review will briefly examine the current state of research in immunotherapies against the 3 most commonly targeted proteins for age-related neurodegenerative disease Aβ, tau, and α-syn. The discussion will then turn to combinatorial strategies that enhance the effects of immunotherapy against aggregating protein, followed by new potential targets of immunotherapy such as aging-related processes.PURPOSE We sought to assess compliance to resuscitation guidelines during pediatric simulated cardiac arrests in a pediatric intensive care unit (PICU) and to identify performance gaps to target with future training. METHODS In a prospective observational study in a PICU, ten cardiac arrest scenarios were developed for resuscitation training and video recorded. The video recordings were examined for times to start cardiopulmonary resuscitation (CPR), delivery of first shock, CPR quality (rate, depth), length of pauses, chest compression fraction (CCF), ventilation, pulse/rhythm assessment, compressors' rotation, and leader's behaviours. The primary outcome was percentage of events compliant to Pediatric Advance Life Support guidelines. RESULTS Compliance to guidelines was poor in the 23 simulation events studied. The median [interquartile range] time to start CPR was 29 [16-76] sec and 320 [245-421] sec to deliver the first shock. A total of 306 30-sec epochs of CPR were analyzed; excellent CPR (≥ 90% compressions in target for rate and depth) was achieved in 22 (7%) epochs.
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