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Ultrasound Microvessel Imaging of the Human Placenta Demonstrates Altered Vessel Densities in Fetal Growth Restriction With Vascular and Immune Pathologies: A Pilot Case-Control Study.
J Ultrasound Med
February 2025
Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota, USA.
Objectives: Fetal growth restriction (FGR) is commonly associated with placental dysfunction, increasing perinatal morbidity and mortality. Visualizing placental vessels in utero would be advantageous for identifying functional FGR cause and determining proper management strategies. We aimed to utilize high-sensitivity ultrasound microvessel imaging (HUMI) for quantifying placental vessel density (VD) in pregnancies diagnosed with FGR.
View Article and Find Full Text PDFSingular-Value-Decomposition-Based Matrix Surgery.
Entropy (Basel)
August 2024
School of Computing, The University of Buckingham, Buckingham MK18 1EG, UK.
This paper is motivated by the need to stabilise the impact of deep learning (DL) training for medical image analysis on the conditioning of convolution filters in relation to model overfitting and robustness. We present a simple strategy to reduce square matrix condition numbers and investigate its effect on the spatial distributions of point clouds of well- and ill-conditioned matrices. For a square matrix, the SVD surgery strategy works by: (1) computing its singular value decomposition (SVD), (2) changing a few of the smaller singular values relative to the largest one, and (3) reconstructing the matrix by reverse SVD.
View Article and Find Full Text PDFSpatiotemporal Expansion of Algal Blooms in Coastal China Seas.
Environ Sci Technol
July 2024
Department of Ocean Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
The coastal seas of China are increasingly threatened by algal blooms, yet their comprehensive spatiotemporal mapping and understanding of underlying drivers remain challenging due to high turbidity and heterogeneous water conditions. We developed a singular value decomposition-based algorithm to map these blooms using two decades of MODIS-Aqua satellite data, spanning from 2003 to 2022. Our findings indicate significant algal activity along the Chinese coastline, impacting an average annual area of approximately 1.
View Article and Find Full Text PDFSingular Value Decomposition-Based Penalized Multinomial Regression for Classifying Imbalanced Medulloblastoma Subgroups Using Methylation Data.
J Comput Biol
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Department of Molecular Biology, National Cancer Institute-University of Gezira, Wad Madani, Sudan.
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View Article and Find Full Text PDFEmploying hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake.
Sci Total Environ
April 2024
Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of CyanoHABs. However, unlike traditional methods such as pigment quantification or microscopy counting, the high-frequency data from in-situ fluorometric sensors display unpredictable fluctuations and variability, posing a challenge for predictive models to discern underlying trends within the time-series sequence.
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