Ultrasound computed tomography (USCT) is an emerging modality to image the acoustic properties of the breast tissue for cancer diagnosis. With the need of improving the diagnostic accuracy of USCT, while maintaining the cost low, recent research is mainly focused on improving (1) the reconstruction methods and (2) the acquisition systems. D-optimal sequential experimental design (D-SOED) offers a method to integrate these aspects into a common systematic framework. The transducer configuration is optimized to minimize the uncertainties in the estimated model parameters, and to reduce the time to solution by identifying redundancies in the data. This work presents a formulation to jointly optimize the experiment for transmission and reflection data and, in particular, to estimate the speed of sound and reflectivity of the tissue using either ray-based or wave-based imaging methods. Uncertainties in the parameters can be quantified by extracting properties of the posterior covariance operator, which is analytically computed by linearizing the forward problem with respect to the prior knowledge about parameters. D-SOED is first introduced by an illustrative toy example, and then applied to real data. This shows that the time to solution can be substantially reduced, without altering the final image, by selecting the most informative measurements.
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http://dx.doi.org/10.1121/1.5122291 | DOI Listing |
J Am Psychiatr Nurses Assoc
January 2025
Ahmad Rayan, RN, CNS, PhD, Zarqa University, Zarqa, Jordan.
Background: Studies have found that trait mindfulness is associated with lower levels of depressive symptoms among people diagnosed with schizophrenia. Still, the role of the perceived public stigma in this association has yet to be established.
Aims: The purpose of this study was to assess the association between mindfulness and depressive symptoms experienced by people diagnosed with schizophrenia, controlling for the impact of their demographics and their perceived public stigma against mental illness.
J Orthop Surg Res
January 2025
The School of Health, Fujian Medical University, Fuzhou, China.
Objectives: This study aimed to examine the relationships between kinesiophobia and injury severity, balance ability, knee pain intensity, self-efficacy, and functional status in patients with meniscus injuries and to identify key predictors of kinesiophobia.
Design: A single-center, prospective cross-sectional study.
Methods: A cross-sectional study involving 123 patients diagnosed with meniscus injuries at Fujian Provincial Hospital was conducted.
BMC Cancer
January 2025
Department of Biomedical Sciences, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, P.O. Box 79, Ethiopia.
Background: Chemotherapy is a well-established therapeutic approach for several malignancies, including breast cancer (BCa). However, the clinical efficacy of this drug is limited by cardiotoxicity. Assessing multiple cardiac biomarkers can help identify patients at risk of adverse outcomes from chemotherapy.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Department of Public Health, College of Health Science, Assosa University, Benishangul-Gumuz region, Assosa Town, Ethiopia.
Background: Adverse birth outcomes are a significant public health problem worldwide, particularly in low- and middle-income countries. Adverse birth outcomes have significant immediate and long-term health consequences for infants and their families. Understanding the determinants of adverse birth outcomes is crucial to effective interventions.
View Article and Find Full Text PDFBMC Public Health
January 2025
School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongdansantiao, Dongcheng district, Beijing, 100730, China.
Introduction: Retirement represents a significant life transition and is associated with individual health outcomes. Previous studies on the health effects of retirement have yielded inconsistent conclusions. This study aimed to estimate the impact of retirement on the body mass index (BMI) and BMI-defined overweight and obesity.
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