Aiming at the frequent failures in the PACS clinical applications, a continuous availability (CA) image server with triple modular redundancy (TMR) is designed and used for failover at the CPU/memory level. The TMR voter, which is included in the CA image server, is applied to detection of failures. Through UW or FW SCSI interfaces, two mirror-image disks, two RAID controllers and two DLT controllers are respectively connected to the modules in the TMR and a complete CA image server is brought into being. The CA image server will replace the potential single point of failure (SPOF) in the PACS and increases its availability rate to 99.999%. The advantages of the TMR CA image server make itself well suitable for large-scale medical image network and database applications.
Download full-text PDF |
Source |
---|
Biomaterials
January 2025
Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun, 130021, PR China; State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun, 130012, PR China. Electronic address:
The kidney, vital for metabolic balance, faces risks of severe diseases if dysfunctional. The glomerular filtration barrier (GFB), crucial for blood filtration, disrupts in conditions like diabetic nephropathy or nephritides, resulting in proteinuria or even renal failure. Monitoring GFB integrity is essential for early diagnosis or prognostic monitoring.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
Cybersecurity Laboratory, Luleå University of Technology, 97187 Luleå, Sweden.
Alzheimer's disease (AD) leads to severe cognitive impairment and functional decline in patients, and its exact cause remains unknown. Early diagnosis of AD is imperative to enable timely interventions that can slow the progression of the disease. This research tackles the complexity and uncertainty of AD by employing a multimodal approach that integrates medical imaging and demographic data.
View Article and Find Full Text PDFBMJ Open
January 2025
Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK.
Background: The primary endpoint in diabetes-related foot ulcer (DFU) trials is often time to healing, defined as complete re-epithelialisation with absence of drainage, requiring clinical expert assessment as the gold standard. Central blinded photograph review for confirmation of healing is increasingly being undertaken for internal validity. The Diabetic Foot Ulcer Photography study aims to determine the agreement between blinded independent review panel members for assessing ulcer healing status in patients with DFUs.
View Article and Find Full Text PDFHeliyon
December 2024
Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, PR China.
Objectives: To clarify the prenatal magnetic resonance (MR) imaging characteristics of fetal intracranial haemorrhages (ICHs) in a large cohort and correlate them with birth outcomes.
Methods: We retrospectively reviewed MR images of fetuses with ICH on screening ultrasound (US) on picture archiving communication system (PACS) servers within a nearly ten-year period from two medical tertiary centres. The indications, main abnormal findings and coexistent anomalies were recorded by two experienced radiologists with census readings.
Heliyon
December 2024
Department of Computer Science & Engineering, K L E F Deemed To Be University, Green Fields, Vaddeswaram, Guntur (dt), Andhra Pradesh, 521230, India.
Real-time monitoring and anomaly detection are essential in healthcare to ensure safe conditions for patients and maintain the integrity of medical data samples. The majority of existing systems, despite improvements in healthcare technologies, cannot capture the spatial and temporal patterns of multimodal data simultaneously, process high Volume data in real-time, and ensure the privacy of patients' identity effectively. In this work, we handle these limitations by proposing a complete approach that uses state-of-the-art deep learning and data processing architectures to realize resilient anomaly detection in healthcare systems.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!