Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from three experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts' measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts' variability range. The platform remains open for new submissions.
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http://dx.doi.org/10.1109/TMI.2015.2503890 | DOI Listing |
BMC Pharmacol Toxicol
January 2025
Department of Pharmaceutics and Pharmaceutical Technology, Kampala International University, Western Campus, P.O. Box 71, Ishaka - Bushenyi, Uganda.
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View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Department of Neuroscience "Rita Levi Montalcini", University of Turin, Via Cherasco 15, Turin, 10126, Italy.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder with both genetic and environmental factors contributing to its pathogenesis. While early-onset AD has well-established genetic determinants, the genetic basis for late-onset AD remains less clear. This study investigates a large Italian family with late-onset autosomal dominant AD, identifying a novel rare missense variant in GRIN2C gene associated with the disease, and evaluates the functional impact of this variant.
View Article and Find Full Text PDFMalar J
January 2025
Department of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Background: The increased occurrence of malaria among Africa's displaced communities poses a new humanitarian problem. Understanding malaria epidemiology among the displaced population in African refugee camps is a vital step for implementing effective malaria control and elimination measures. As a result, this study aimed to generate comprehensive and conclusive data from diverse investigations undertaken in Africa.
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Medical Big Data Research Center, Medical Innovation Research Division, Chinese PLA General Hospital, 28 Fuxing RD., Beijing, 100853, China.
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BMC Endocr Disord
January 2025
The First School of Clinical Medicine, Lanzhou University, No.199 Donggang West Road, Chengguan District, Lanzhou, Gansu Province, 730000, China.
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