With the utilization of diffusion tensor information of image voxels, a novel MRF (Markov Random Field) segmentation algorithm was proposed for diffusion tensor MRI (DT-MRI) images benefitted from the introduction of Frobenius norm. The comparison of the segmentation effects between the proposed algorithm and K-means segmentation algorithm for DT-MRI image was made, which showed that the new algorithm could segment the DT-MRI images more accurately than the K-means algorithm. Moreover, with the same segmentation algorithm of MRF, better outcomes were achieved in DT-MRI than in conventional MRI (T2WI) image.
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J Food Sci
January 2025
College of Electronics and Engineering, Heilongjiang University, Harbin, China.
Bruises can affect the appearance and nutritional value of apples and cause economic losses. Therefore, the accurate detection of bruise levels and bruise time of apples is crucial. In this paper, we proposed a method that combines a self-designed multispectral imaging system with deep learning to accurately detect the level and time of bruising on apples.
View Article and Find Full Text PDFEJNMMI Phys
January 2025
Institute of Radiology, Nuclear Medicine and Molecular Imaging, Heart and Diabetes Center North Rhine-Westphalia, University Hospital (Ruhr University Bochum), Medical Faculty OWL (Bielefeld University), Bad Oeynhausen, Germany.
Background: The topic of the effect of the patient table on attenuation in myocardial perfusion imaging (MPI) SPECT is gaining new relevance due to deep learning methods. Existing studies on this effect are old, rare and only consider phantom measurements, not patient studies. This study investigates the effect of the patient table on attenuation based on the difference between reconstructions of phantom scans and polar maps of patient studies.
View Article and Find Full Text PDFJ Assist Reprod Genet
January 2025
Reproductive Medicine Department, Villa Mafalda, Via Monte Delle Gioie 5, 00199, Rome, Italy.
Purpose: Analyze morphokinetic, morphology, and KIDscore™Day5 in different PGT-A classes, focusing on putative mosaicism level and type.
Methods: The single-center retrospective study analyzed 832 embryoscope-cultured blastocysts from cycles with at least one putative mosaic, conducted from 2020 to 2022. A P-value < 0.
Biomed Phys Eng Express
January 2025
Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA, United States of America.
This study aimed to develop and evaluate an efficient method to automatically segment T1- and T2-weighted brain magnetic resonance imaging (MRI) images. We specifically compared the segmentation performance of individual convolutional neural network (CNN) models against an ensemble approach to advance the accuracy of MRI-guided radiotherapy (RT) planning..
View Article and Find Full Text PDFBackground: Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. Artificial Intelligence (AI)-based medical image analysis has the potential to augment the clinical management of IPMNs by improving diagnostic accuracy.
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