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Computer vision based automatic evaluation method of YO steel coating performance with SEM image.
Sci Rep
January 2025
State Key Laboratory of Baiyunobo Rare Earth Resource Researches and Comprehensive Utilization, Baotou Research Institute of Rare Earths, Baotou, 014030, China.
This study introduces a deep learning-based automatic evaluation method for analyzing the microstructure of steel with scanning electron microscopy (SEM), aiming to address the limitations of manual marking and subjective assessments by researchers. By leveraging advanced computer vision algorithms, specifically a suitable model for long-term dendritic solidifications named Tang Rui Detect (TRD), the method achieves efficient and accurate detection and quantification of microstructure features. This approach not only enhances the training process but also simplifies loss function design, ultimately leading to a proper evaluation of surface modifications in steel materials.
View Article and Find Full Text PDFComparative evaluation of two simulation technologies for obstetric ultrasound trainees' assessment.
Eur J Obstet Gynecol Reprod Biol
January 2025
Department of Obstetrics and Gynecology, Port-Royal Maternity, Cochin Hospital, Paris Cité University, APHP, Paris, France.
Objective: The objective was to evaluate the performance of two different obstetric ultrasound simulators in assessing the practical skills of trainees compared to the standard method of practical assessment conducted on pregnant women volunteers.
Methods: We performed a prospective observational study. Two simulators were compared: the Simbionix simulator which uses a mannequin and heteroevaluation and the OPUS simulator which uses optical positioning technology with automatic assessment.
White matter hyperintensities regress at a high rate at three months after minor ischemic stroke or transient ischemic attack.
J Neuroradiol
January 2025
Soochow Medical college of Soochow University, Suzhou, PR China; Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, PR China. Electronic address:
Background: The potential for early white matter hyperintensities(WMH) regression and associated contributory factors remains uncertain. The purpose of this study is to investigate whether WMH regress at early time of three months after minor ischemic stroke (MIS) or transient ischemic attack (TIA), while also identifying factors that may influence this outcome.
Methods: A retrospective analysis of a prospective subcohort from the CHANCE trial comprising individuals with MIS and TIA was conducted.
Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.
MAGMA
January 2025
Aix Marseille Univ, CNRS, CRMBM, Marseille, France.
Objective: Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness in this field. However, the impact of reducing neural network complexity remains unexplored in the FF quantification in individual muscles.
View Article and Find Full Text PDFAutomatic 4D mitral valve segmentation from transesophageal echocardiography: a semi-supervised learning approach.
Med Biol Eng Comput
January 2025
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Performing automatic and standardized 4D TEE segmentation and mitral valve analysis is challenging due to the limitations of echocardiography and the scarcity of manually annotated 4D images. This work proposes a semi-supervised training strategy using pseudo labelling for MV segmentation in 4D TEE; it employs a Teacher-Student framework to ensure reliable pseudo-label generation. 120 4D TEE recordings from 60 candidates for MV repair are used.
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