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Multimodal multiview bilinear graph convolutional network for mild cognitive impairment diagnosis.
Biomed Phys Eng Express
January 2025
Shandong University of Traditional Chinese Medicine, Qingdao Academy of Chinese Medical Sciences, Jinan, Shandong, 250355, CHINA.
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease, and it can be used as an important indicator of disease progression. However, many existing methods focus mainly on the image itself when processing brain imaging data, ignoring other non-imaging data (e.g.
View Article and Find Full Text PDFIn utero progression of cephaloceles: prenatal to postnatal analysis.
J Neurosurg Pediatr
January 2025
1Division of Neurosurgery, Department of Surgery, Children's Hospital of Philadelphia.
Objective: The natural history of cephaloceles is not well understood. The goal of this study was to better understand the natural history of fetal cephaloceles from prenatal diagnosis to the postnatal period.
Methods: Between January 2013 and April 2023, all patients evaluated with a cephalocele at the Center for Fetal Diagnosis and Treatment were identified.
Correlation between MRI findings of pituitary gland and prolactin level among hyperprolactinemia adult female Saudi patients in rural areas: A retrospective multicentric study.
Medicine (Baltimore)
January 2025
Department of Urology, School of Medicine, Ibb University, Ibb, Yemen.
Identifying the prolactin threshold that necessitates pituitary magnetic resonance imaging (MRI) in patients with hyperprolactinemia remains challenging. Therefore, developing standards for serum prolactin level criteria to predict prolactinoma is critical. This study aimed to investigate the correlation between hyperprolactinemia and the presence of pituitary adenoma among Saudi female patients with verified prolactin levels.
View Article and Find Full Text PDFSemi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data.
J Magn Reson Imaging
January 2025
Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway.
Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.
Purpose: This work tests the viability of semi-supervision for brain metastases segmentation.
Visualizing Preosteoarthritis: Updates on UTE-Based Compositional MRI and Deep Learning Algorithms.
J Magn Reson Imaging
January 2025
Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is crucial for early proactive management and limit growing disease burden. The more recent advanced quantitative imaging techniques and deep learning (DL) algorithms in musculoskeletal imaging have shown great potential for visualizing "pre-OA.
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