Background: Children with forehead port-wine stains (PWSs) are at risk of Sturge-Weber syndrome (SWS). However, most will not develop neurologic manifestations.
Objective: To identify children at greatest risk of SWS.
Method: In this retrospective cohort study of children with a forehead PWS, PWSs were classified as "large segmental" (half or more of a contiguous area of the hemiforehead or median pattern) or "trace/small segmental" (less than half of the hemiforehead). The outcome measure was a diagnosis of SWS.
Results: Ninety-six children had a forehead PWS. Fifty-one had a large segmental PWS, and 45 had a trace/small segmental PWS. All 21 children with SWS had large segmental forehead PWSs. Large segmental forehead PWSs had a higher specificity (0.71 vs 0.27, P < .0001) and a higher positive predictive value (0.41 vs 0.22, P < .0001) for SWS than any forehead involvement by a PWS.
Limitations: Retrospective study at a referral center.
Conclusion: Children with large segmental forehead PWSs are at highest risk of SWS.
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http://dx.doi.org/10.1016/j.jaad.2020.05.017 | DOI Listing |
J Imaging Inform Med
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Faculty of Medicine and Pharmacy of Rabat, Mohammed V University of Rabat, Rabat, 10000, Morocco.
Gastrointestinal (GI) disease examination presents significant challenges to doctors due to the intricate structure of the human digestive system. Colonoscopy and wireless capsule endoscopy are the most commonly used tools for GI examination. However, the large amount of data generated by these technologies requires the expertise and intervention of doctors for disease identification, making manual analysis a very time-consuming task.
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January 2025
Colloid Chemistry, Department of Chemistry, University of Konstanz, Universitaetsstrasse 10, 78464, Konstanz, Germany.
Complex structures can be understood as compositions of smaller, more basic elements. The characterization of these structures requires an analysis of their constituents and their spatial configuration. Examples can be found in systems as diverse as galaxies, alloys, living tissues, cells, and even nanoparticles.
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January 2025
Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City, 243, Taiwan.
This study develops the you only look once segmentation (YOLOSeg), an end-to-end instance segmentation model, with applications to segment small particle defects embedded on a wafer die. YOLOSeg uses YOLOv5s as the basis and extends a UNet-like structure to form the segmentation head. YOLOSeg can predict not only bounding boxes of particle defects but also the corresponding bounding polygons.
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January 2025
Department of Neurosurgery, University Hospital Tübingen, Tübingen, Germany.
To compare 1D (linear) tumor volume calculations and classification systems with 3D-segmented volumetric analysis (SVA), focusing specifically on their effectiveness in the evaluation and management of NF2-associated vestibular schwannomas (VS). VS were clinically followed every 6 months with cranial, thin-sliced (< 3 mm) MRI. We retrospectively reviewed and used T1-weighted post-contrast enhanced (gadolinium) images for both SVA and linear measurements.
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Department of Trauma and Reconstructive Surgery, BG Hospital Bergmanntrost, Merseburger Straße 165 06112 Halle, Halle, Sachsen-Anhalt, 06112, GERMANY.
The purpose of this study was to develop a robust deep learning approach trained with a small in-vivo MRI dataset for multi-label segmentation of all eight carpal bones for therapy planning and wrist dynamic analysis. Approach: A small dataset of 15 3.0-T MRI scans from five health subjects was employed within this study.
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