Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Two-dimensional transvaginal ultrasound (2D) is typically performed to monitor follicle growth in IVF and to determine the optimal time for administering human chorionic gonadotrophin. However, 2D only provides an approximation of the real volume of follicles and therefore cannot be used to guarantee standards for follicular measurement. The automated measurement of follicular size in three dimensions (3D) using a software programme that identifies and quantifies hypoechoic regions within a 3D dataset might provide an objective, fast, valid and reliable standard for such measurements. A prospective controlled study (group I: 20 patients, 2D; group II: 20 patients, 3D) investigated how the criteria for triggering oocyte maturation that are normally used in 2D compare to the new and more accurate method of measuring follicles using 3D-based automated volume count. Significantly more oocytes were fertilized (group 1: 7.1 +/- 4.5, group 2: 11.5 +/- 6.4; P < 0.03) when using 3D technology and automated volume count. The study assumes that the automated volume count more closely mirrors the biological reality, which means that it can also be used to guarantee the quality standards established by the European Union directive on tissues and cells (2004/23/EC). This new technology therefore holds great promise of becoming the new standard for monitoring follicular growth in IVF.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.rbmo.2009.09.008 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Out-of-the-Box Large Language Models for Detecting and Classifying Critical Findings in Radiology Reports Using Various Prompt Strategies.
AJR Am J Roentgenol
September 2025
Department of Radiology, Stanford University, Stanford, CA, USA.
The increasing complexity and volume of radiology reports present challenges for timely critical findings communication. To evaluate the performance of two out-of-the-box LLMs in detecting and classifying critical findings in radiology reports using various prompt strategies. The analysis included 252 radiology reports of varying modalities and anatomic regions extracted from the MIMIC-III database, divided into a prompt engineering tuning set of 50 reports, a holdout test set of 125 reports, and a pool of 77 remaining reports used as examples for few-shot prompting.
View Article and Find Full Text PDFImplementation of intelligent All-in-one technology in rectal cancer radiotherapy: A retrospective study on automation efficiency and safety.
J Appl Clin Med Phys
September 2025
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Clinical Research Center for Radiation Oncology, Shanghai Key Laboratory of Radiation Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Purpose: This study aims to assess percentage of automated AIO plans that met clinical treatment standards of radiotherapy plans generated by the fully automated All-in-one (AIO) process.
Methods: The study involved 117 rectal cancer patients who underwent AIO treatment. Fully automated regions of interest (ROI) and treatment plans were developed without manual intervention, comparing them to manually generated plans used in clinical practice.
Integrating rule-based NLP and large language models for statin information extraction from clinical notes.
Int J Med Inform
September 2025
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. Electronic address:
Background: Identifying patient-specific barriers to statin therapy, such as intolerance or deferral, from clinical notes is a major challenge for improving cardiovascular care. Automating this process could enable targeted interventions and improve clinical decision support (CDS).
Objective: To develop and evaluate a novel hybrid artificial intelligence (AI) framework for accurately and efficiently extracting information on statin therapy barriers from large volumes of clinical notes.
Automated volumetric MRI quantification of body fat and skeletal muscle in the UK Biobank: technical validation against expert manual segmentations and comparison with single-slice techniques.
Abdom Radiol (NY)
September 2025
Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK.
Objectives: The escalating global incidence of obesity, cardiometabolic disease and sarcopenia necessitates reliable body composition measurement tools. MRI-based assessment is the gold standard, with utility in both clinical and drug trial settings. This study aims to validate a new automated volumetric MRI method by comparing with manual ground truth, prior volumetric measurements, and against a new method for semi-automated single-slice area measurements.
View Article and Find Full Text PDFDevelopment and Implementation of an Ambulatory Orders-Based Ophthalmology Imaging Workflow.
J Imaging Inform Med
September 2025
Department of Radiology, University of Cincinnati, Cincinnati, OH, USA.
Background: Ocular imaging is essential to the diagnosis and management of eye disease, yet standardized imaging workflows remain underdeveloped in the eye care setting. This manuscript describes the design and implementation of an orders-based imaging workflow for ambulatory ophthalmology integrated with the electronic health record and enterprise imaging systems.
Methods: We developed a DICOM-compliant workflow for pediatric ophthalmology imaging that supports HL7 integration, DICOM modality worklists, and enterprise archive storage.