قدرت تفکیک دستگاه طیف‌نگار جرمی به صورت مستقیم شدت یون خروجی و انرژی آن بستگی دارد. مقدار تولید شده جریان باریکه الکترونی وابسته است. از جمله وظایف مدار کنترل چشمه برخورد تنظیم برای رسیدن بهینه می‌باشد. در ساخت پارامترهایی نظیر تثبیت آن، دقیق پتانسل الکتریکی لنز الکترودهای یونی بسیار حایز اهمیت این مقاله با قابلیت انتشار الکترون، پتانسیل نقاط طراحی ساخته شد. کنترلر بر روی طیف نگار 44Varian MAT ...

The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face detection algorithms derived from MRF considerations. For enhanced detection, the MRF models are defined for every permutation of site indices in the image. We find the optimal permutation that provides maximum discrim...

S.Z. Li, Y.H. Huang, J.S. Fu School of Electrical and Electronic Engineering, Nanyang Technological University Nanyang Avenue, Singapore 2263 ABSTRACT A general de nition of convex potential functions is given for discontinuity-preserving MRF restoration models. This gives a class of Bayesian MRF models which satisfy several desirable analytical and computational properties for regularization o...

Current routine MRI examinations rely on the acquisition of qualitative images that have a contrast "weighted" for a mixture of (magnetic) tissue properties. Recently, a novel approach was introduced, namely MR Fingerprinting (MRF) with a completely different approach to data acquisition, post-processing and visualization. Instead of using a repeated, serial acquisition of data for the characte...

OBJECTIVE Previous studies have demonstrated that immune complexes (ICs) may be involved in the pathogenesis of rheumatoid arthritis (RA). However, autoantigens contained in rheumatoid ICs remain to be elucidated. In the present study, we investigated whether the peptides captured by C1q and monoclonal rheumatoid factor (mRF), presumably associated with ICs, were citrullinated in synovial fluid...

Recent advances in multi-atlas based algorithms address many of the previous limitations in model-based and probabilistic segmentation methods. However, at the label fusion stage, a majority of algorithms focus primarily on optimizing weight-maps associated with the atlas library based on a theoretical objective function that approximates the segmentation error. In contrast, we propose a novel ...

A supervised classification method based on AdaBoost posterior probability and Markov Random Fields (MRF) model with Linear Targets Prior (LTP) is proposed in this paper. Firstly in contrast with most existing regions (superpixels) based models, this approach captures contiguous image regions called superpixels from ratio response maps of original images. Secondly, Adaboost classifier is employ...