An automatic algorithm based on wavelet fusion is proposed for segmenting brain glioma with blurred boundaries and complex intratumoral structures on multimodal magnetic resonance (MR) images. Firstly, the T1, T1ce, T2 and Flair MR images of brain glioma are fused with the bias field corrected. Secondly, the image blocks to be classified are extracted, and the 3D-UNet network is trained to classify the pixels in the image blocks. Finally, the trained network model is used for segmentation, and the contour extraction method based on connected regions is used to reduce false positives. The average segmentation accuracy (DSC) of the whole, core and edema parts of the tumors was found to be 90.64%, 80.74% and 86.37%, respectively. The results indicated that the accuracy of the algorithm proposed was similar with or higher than the gold standard method. Compared with the method without multimodal image fusion, the algorithm proposed not only reduced the amount of data and redundant information in the input network, but also improved the accuracy and robustness of segmentation.

The specific absorption rate (SAR) needs to be estimated for safety concerns when performing high-field magnetic resonance imaging (MRI) on knee joint. Electromagnetic simulation can be used to calculate the local SAR on knees if a patient-specific knee model is available. In this work, a method for rapid construction of knee models from low-field magnetic resonance knee images was proposed. A convolutional neural network (CNN) was first used to segment the sagittal T₁-weighted spin echo images of knees into fat, bone and muscle. All the pixels other than those from the fat and bone are classified as muscle pixels. The U-Net network, a full CNN with a convolutional layer number of four and adopting a cross entropy function, was used to perform segmentation slice-by-slice. The results from automatic segmentation were compared with those obtained with manual delineation with quantitative measures. Moreover, SAR with a 3 T quadrature birdcage coil was calculated. The simulation results validated the proposed method by showing that and a relatively accurate local SAR estimation could be obtained with the knee models constructed from low-field knee images.

Interpreting magnetic resonance imaging (MRI) data by radiologists is time consuming and demands special expertise. Diagnosis of prostate cancer (PCa) with deep learning can also be time consuming and data storage consuming. This work presents an automated method for PCa detection based on cascaded convolutional neural network (CNN), including pre-network and post-network. The pre-network is based on a Faster-RCNN and trained with prostate images in order to separate the prostate from nearby tissues; the ResNet-based post-network is for PCa diagnosis, which is connected by bottlenecks and improved by applying batch normalization (BN) and global average pooling (GAP). The experimental results demonstrated that the cascaded CNN proposed had a good classification results on the in-house datasets, with less training time and computation resources.

Formation porosity can be calculated from one-dimensional nuclear magnetic resonance (NMR) logging data with a fixed cutoff value and the volume model of conventional logging data. However, the porosity calculated with this method often appears to be overestimated in the enlarged hole section. In this work, the calculation methods for T₂ and T₁ nuclear magnetic porosity from NMR results of core samples and two-dimensional NMR logging data were investigated. Firstly, the characteristics of NMR relaxation spectra of fluids at different pore sizes were obtained and used to analyze the distribution range of pore diameter and affecting factors of the cutoff value of the drilling fluid peak. A model for estimating the cutoff value of the drilling fluid relaxation time was then established. A method for calculating the effective porosity was then proposed with variable cutoff value of clay bond water relaxation time, according to the deterministic principle about cutoff value of clay bond water relaxation time in un-enlarged and enlarged hole section. The method proposed was applied to the data from many wells, and demonstrated better accuracy than the traditional method using T₁ distribution spectra. The method can effectively solve the problem of overestimated porosity in the enlarged hole section and meet the requirement for reservoir evaluation.

In order to study the effect of echo time (T_E) on nuclear magnetic resonance (NMR) porosity in tight oil (gas) and shale reservoir, multi-T_E NMR experiments and NMR numerical simulations were performed on CuSO₄ solutions with specific transversal relaxation time (T₂). The results showed that the normalization NMR porosity of different T₂ relaxation components remained 100% in the low T_E region, and rapidly decreased with increasing T_E. When T_E was greater than certain value, the normalization NMR porosity dropped to zero. However, the T_E value at which the normalization NMR porosity began to decrease and the T_E value at which the normalization NMR porosity dropped to zero were different for different NMR relaxation component. Moreover, the whole NMR measurement was divided into lossless zone, fast decay zone, invalid parameter zone and instrument blind zone, based on the relationships between the normalization NMR porosity of different relaxation component and T_E. For each specific relaxation component, a logarithmic relationship was demonstrated between the loss of relaxation component and T_E in the fast decay zone. A method for NMR porosity correction was given.

The long-life nuclear spin singlet states (LLSs) have broad application prospects due to the unique nature of their long lifetime. Herein, in a solution of alanylglycylgcine (AGG), the nuclear spin singlet state of a two-spin system far from the chiral carbon in the structure is prepared. Then, the effects of sample concentration, temperature, radiofrequency (RF) center, J-coupling value and magnetic field inhomogeneity on conversion efficiency and lifetime of the LLSs were investigated. The experimental results showed that the conversion efficiency and lifetime of the singlet state were not affected by the sample concentration and magnetic field inhomogeneity, but increased with increasing experimental temperature. The influence of the position of RF center on the singlet state was not obvious when it changed within a small range, but the conversion efficiency and lifetime reduced significantly when the changes were large. Moreover, the singlet state was found to be sensitive to the changes of J-coupling value. The conversion efficiency and lifetime reduced significantly with choose of non-accurate J-coupling constant.

The amount of sample tubes used in liquid-state nuclear magnetic resonance (NMR) experiments is large. It is often required that the sample tubes are cleaned and re-used. The cleaning efficiency and the degree of cleanness after cleaning directly affect the results of subsequent experiments. In the meanwhile, the waste produced during the cleaning process pollute the environment. In this work, a hand-held portable high-pressure cleaner for NMR sample tubes is developed, with its structure and function described in detail. Then, sample tubes with different solvents and solutions were cleaned with this apparatus and commercial NMR sample tube cleaning apparatus. The cleaning efficiency and cleanness were compared. Lastly, the degree of wear and tear on the NMR sample tube was evaluated after cleaning. The results demonstrated that the apparatus proposed in this work had a high cleaning performance and efficiency for the NMR sample tubes without heavy contamination, and caused less damage. The cleaning process does not require the use of any toxic organic solvent such that it is environment friendly.

A hydrogen maser confines hydrogen atoms in the storage bulb and produces self-sustained oscillation in a low-loss resonance cavity. In this work, a miniaturized hydrogen maser was designed and fabricated utilizing a dielectric loaded cavity having a low frequency-temperature coefficient. The frequency stability and accuracy of the hydrogen maser were analyzed. The experimentally measured atomic storage time of the hydrogen maser was 0.4 s, and the frequency stability 5.6×10^-15/(1 000 s), agreeing with the design.

The microwave probing signal of the rubidium atomic frequency standard (RAFS) is used to excite the transitions between the ground-state energy levels of rubidium atoms, and realize resonance detection. At present, the microwave generation schemes commonly used all have the disadvantages of complicated circuit structure, high power consumption and inconvenient integration. This work introduces a design scheme for generating discontinuous microwave inquiry signal using the phase-locked loop (PLL) technology. The scheme takes the 10 MHz signal as a reference frequency, and is capable of obtain the (6 834.687 5 MHz ±f_M) signal directly under a reasonable configuration of single chip microcomputer. The scheme has the advantages of simple circuit structure, low power consumption and high digitization. The stability of the whole machine was found to be better than 1.5E-11/√τ(1 s ≤ τ ≤ 100 s). The performance indexes can meet the requirements of small commercial rubidium atomic clock.

A novel proton nuclear magnetic resonance (¹H NMR) method for determining the absolute content of ticagrelor was proposed. The ideal spectra were obtained on a Bruker Avance-300 spectrometer with deuterated methanol (CD₃OD) as the solvent and sulfadoxin as the internal standard. The ticagrelor signals at δ_H 7.14 (2H, m) and δ_H 7.04 (1H, s), as well as those of sulfadoxin at δ_H 8.04 (1H, s), δ_H 7.73 (2H, d) and δ_H 6.54 (2H, d), were selected for quantitative analysis. The detection conditions were as following:probe temperature 308 K, spectrum width 3 511.5 Hz, center frequency 1 470.6 Hz, pulse angle θ=30°, delay time (d1) 10 s, number of scans 16 and line broadening 0.3 Hz. The signals from ticagrelor and internal standard sulfadoxin showed good separation, precision, reproducibility, and wide linearity ranges with Y=1.053X-0.081 (r=0.996, n=5). The content of ticagrelor was estimated to be 99.4% (RSD=0.20%). This method was proven simple, accurate and rapid.

Cyflumetofen is a new type of acaricide with high efficiency and low residue. In this work, the compound was characterized by infrared absorption (IR), ultraviolet absorption (UV) and mass spectrometry, as well as nuclear magnetic resonance spectroscopy (¹H NMR, ¹³C NMR, DEPT, ¹H-¹H COSY, ¹H-¹³C HSQC and ¹H-¹³C HMBC). The characteristic absorption peaks in the UV and IR spectra were discussed. The ¹H and ¹³C NMR signals of cyflumetofen were assigned, and the two-dimensional signals were used to elucidate its structure.

Nuclear magnetic resonance spectroscopy, especially in vivo proton magnetic resonance spectrum (¹H MRS) and proton nuclear magnetic resonance (¹H NMR), has been increasingly used in brain science researches. There are pros and cons in ¹H MRS and ¹H NMR with respect to experiment design, sample preparation and data processing. In this review, we summarized and discussed the recent progresses of these two techniques in the ends of application range, sample preparation, quantification and data analysis. The work will provide a reference and insights for neuroscience researchers who are interested in using magnetic resonance spectroscopy for metabolic studies of the brain.

Human brain atlases constructed from magnetic resonance images are extremely important for brain and cognition researches. With these atlases or brain maps, researchers can accurately analyze and compare different brain images. In this paper, the research progresses of brain atlas construction from magnetic resonance images are reviewed. Firstly, the development of human brain atlases from magnetic resonance images was introduced, including the technical skills required as well as the limitations. Then the basic technical methods for atlas construction are described. Finally, the statistical methods used for quantitative atlas-based analysis were reviewed, such as voxel-based morphometry and tract-based spatial statistical analysis. By analyzing the current research status, the limitations in the existing methodology and the trend of future development were put forward.