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A feature-based approach for atlas selection in automatic pelvic segmentation.
PLoS One
January 2025
Department of Radiation Physics, Zhejiang Key Laboratory of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
Accurate and efficient automatic segmentation is essential for various clinical tasks such as radiotherapy treatment planning. However, atlas-based segmentation still faces challenges due to the lack of representative atlas dataset and the computational limitations of deformation algorithms. In this work, we have proposed an atlas selection procedure (subset atlas grouping approach, MAS-SAGA) which utilized both image similarity and volume features for selecting the best-fitting atlases for contour propagation.
View Article and Find Full Text PDFSensitivity of anti-filarial antibodies for lymphatic filariasis surveillance: Insights from a serological survey in Samoa in 2018.
PLoS Negl Trop Dis
January 2025
UQ Centre for Clinical Research, Faculty of Health, Medicine, and Behavioural Sciences, The University of Queensland, Brisbane, Queensland, Australia.
Background: Sensitive diagnostic tools that signal lymphatic filariasis (LF) transmission are needed to monitor the progress of LF elimination programs. Anti-filarial antibody (Ab) markers could be more sensitive than antigen (Ag) point-of-care tests for monitoring LF transmission in some settings. This study aimed to investigate the sensitivity of anti-filarial Abs for detecting signals of LF transmission in Samoa by i) investigating the sensitivity and specificity of Ab to identify Ag-positives; ii) estimating the average number needed to test (NNTestav) to identify LF-seropositives (seropositive for Ag and/or any Ab), and iii) compare the efficiency of the different serological indicators by target age group and sampling design.
View Article and Find Full Text PDFSAASNets: Shared attention aggregation Siamese networks for building change detection in multispectral remote sensing.
PLoS One
January 2025
Zhanhua District Power Supply Company, Binzhou, China.
Interfered by external factors, the receptive field limits the traditional CNN multispectral remote sensing building change detection method. It is difficult to obtain detailed building changes entirely, and redundant information is reused in the encoding stage, which reduces the feature representation and detection performance. To address these limitations, we design a Siamese network of shared attention aggregation to learn the detailed semantics of buildings in multispectral remote sensing images.
View Article and Find Full Text PDFDetecting low birth weight is crucial for early identification of at-risk pregnancies which are associated with significant neonatal and maternal morbidity and mortality risks. This study presents an efficient and interpretable framework for unsupervised detection of low, very low, and extreme birth weights. While traditional approaches to managing class imbalance require labeled data, our study explores the use of unsupervised learning to detect anomalies indicative of low birth weight scenarios.
View Article and Find Full Text PDFA new HCM heart sound classification method based on weighted bispectrum features.
Phys Eng Sci Med
January 2025
School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China.
Hypertrophic cardiomyopathy (HCM), including obstructive HCM and non-obstructive HCM, can lead to sudden cardiac arrest in adolescents and athletes. Early diagnosis and treatment through auscultation of different types of HCM can prevent the occurrence of malignant events. However, it is challenging to distinguish the pathological information of HCM related to differential left ventricular outflow tract pressure gradients.
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