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Iterative clustering material decomposition aided by empirical spectral correction for photon counting detectors in micro-CT.
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University of Houston, Department of Physics, Houston, Texas, United States.
Purpose: Photon counting detectors offer promising advancements in computed tomography (CT) imaging by enabling the quantification and three-dimensional imaging of contrast agents and tissue types through simultaneous multi-energy projections from broad X-ray spectra. However, the accuracy of these decomposition methods hinges on precise composite spectral attenuation values that one must reconstruct from spectral micro-CT. Errors in such estimations could be due to effects such as beam hardening, object scatter, or detector sensor-related spectral distortions such as fluorescence.
View Article and Find Full Text PDFCorrigendum to "Retrospective review of seven patients with obesity simultaneously treated with a combination of a glucagon-like peptide-1 receptor agonist and a meal replacement product" [Obesity Pillars 12C (2024) 100138].
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[This corrects the article DOI: 10.1016/j.obpill.
View Article and Find Full Text PDFNoise-robust consistency regularization for semi-supervised semantic segmentation.
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December 2024
Deep Mining and Rock Burst Research Branch, Chinese Institute of Coal Science, Qingniangou Road No. 5, Beijing, 100013, China.
The essential of semi-supervised semantic segmentation (SSSS) is to learn more helpful information from unlabeled data, which can be achieved by assigning adequate quality pseudo-labels or managing noisy pseudo-labels during training. However, most relevant state-of-the-art (SOTA) methods are mainly devoted to improving one aspect. By revisiting the representative SSSS methods from a robust learning view, this paper discovers that the appropriate combination of multiple noise-robust methods contributes both to assigning sufficient quality pseudo labels and managing noisy labels.
View Article and Find Full Text PDFBiomechanical analysis of scoliosis correction under the influence of muscular and external forces.
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Institute of Mechanical Engineering, Dalian Jiaotong University, Dalian 116028, Liaoning, China.
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View Article and Find Full Text PDFAutomatic calculation method for stenosis ratio based on dialysis access ultrasound image segmentation.
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Department of Echocardiography, Ultrasound Diagnostic Center, The First Hospital of Jilin University, Changchun, China.
Background: Dialysis Access (DA) stenosis impacts hemodialysis efficiency and patient health, necessitating exams for early lesion detection. Ultrasound is widely used due to its non-invasive, cost-effective nature. Assessing all patients in large hemodialysis facilities strains resources and relies on operator expertise.
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