Purpose: To evaluate the ability of automated software to quantify uterine peristalsis on cine magnetic resonance imaging (MRI).
Materials And Methods: At 1.5T, half-Fourier acquisition single-shot turbo spin echo (HASTE) techniques were used to obtain 60 serial images over 3 minutes (TR/TE 3000/80 msec) in a midsagittal plane of the uterus. Thirty-two cine MR datasets, obtained from 16 healthy females, were analyzed. Uterine peristalsis was defined as the traveling waves of decreasing signal intensity on the endometrium-junctional zone border. The software detected traveling waves by identifying the neighboring areas showing similar patterns of signal intensity decrease in a different timing. Quantification of uterine peristaltic wave using the fully automated software was compared to qualitative visual evaluation by two readers.
Results: The mean number (and standard deviation) of peristaltic waves detected by the fully automated software and visual evaluations (readers 1 and 2) were 5.4 (3.0), 4.7 (3.1), and 4.5 (3.1) per 3 minutes, respectively. Quantification by fully automated software demonstrated excellent agreement with repeated measurement (weighted kappa 0.99) and with qualitative visual evaluations (range 0.89-0.95), comparable to interreader agreement by visual evaluations (range 0.89-0.93).
Conclusion: The fully automated software can be used to quantify uterine peristalsis comparable to visual evaluation.
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Sci Rep
December 2024
Department of Public Health, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, 1111 Xianxia Road, Shanghai, 200335, China.
Breast ultrasound is recommended for early breast cancer detection in China, but the rapid increase in imaging data burdens sonographers. This study evaluated the agreement between artificial intelligence (AI) software and sonographers in analyzing breast nodule features. Breast ultrasound images from two hospitals in Shanghai were analyzed by both the software and the sonographers for features including echotexture, echo pattern, orientation, shape, margin, calcification, and posterior echo attenuation.
View Article and Find Full Text PDFForensic Sci Int
December 2024
Criminal Investigation School, Southwest University of Political Science and Law, Chongqing, China; Chongqing Institutions of Higher Education Municipal Key Criminal Technology Laboratory, Chongqing, China; Intelligent Research Center of Difficult Homicide Cases Investigation, Southwest University of Political Science and Law, Chongqing, China. Electronic address:
In criminal investigations, distinguishing between impact spatters and fly spots presents a challenge due to their morphological similarities. Traditional methods of bloodstain pattern analysis (BPA) rely significantly on the expertise of professional examiners, which can result in limitations including low identification efficiency, high misjudgment rates, and susceptibility to external disturbances. To enhance the accuracy and scientific rigor of identifying impact spatters and fly spots, this study employed artificial intelligence techniques in image recognition and transfer learning.
View Article and Find Full Text PDFAnal Chem
December 2024
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1, Canada.
Mass spectrometry (MS)-based metabolomics often rely on separation techniques when analyzing complex biological specimens to improve method resolution, metabolome coverage, quantitative performance, and/or unknown identification. However, low sample throughput and complicated data preprocessing procedures remain major barriers to affordable metabolomic studies that are scalable to large populations. Herein, we introduce PeakMeister as a new software tool in the R statistical environment to enable standardized processing of serum metabolomic data acquired by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), a high-throughput separation platform (<4 min/sample) which takes advantage of a serial injection format of 13 samples within a single analytical run.
View Article and Find Full Text PDFPLOS Digit Health
December 2024
Department of Family Medicine, McMaster University, Ontario, Canada.
The Community Paramedicine at Clinic (CP@clinic) program is a community program that utilizes community paramedics to support older adults in assessing their risk factors, managing their chronic conditions, and linking them to community resources. The aim of this project is to design a low-cost, portable, secure, user-friendly database for CP@clinic sessions and pilot test the database with paramedics and older adult volunteers. The CP@clinic program database using the Microsoft Access software was first developed through consultation with the CP@clinic research team.
View Article and Find Full Text PDFMethods Mol Biol
December 2024
School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand.
The detached leaf assay is a valuable method for studying plant-pathogen interactions, enabling the assessment of pathogenicity, plant resistance, and treatment effects. In this protocol, we outline how to set up a Phytophthora detached leaf assay and use non-expert machine learning tools to increase the reliability and throughput of the image analysis. Utilizing ilastik for pixel classification and Python scripts for segmentation, manual correction, and temporal linking, the pipeline provides objective and quantitative data over time.
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