Energy Spectrum Curve Research Articles

Spectral CT-based nomogram for preoperative prediction of Lauren classification in locally advanced gastric cancer: a prospective study.

To develop a nomogram based on clinical features and spectral quantitative parameters to preoperatively predict the Lauren classification for locally advanced gastric cancer (LAGC). Patients diagnosed with LAGC by postoperative pathology who underwent abdominal triple-phase enhanced spectral computed tomography (CT) were prospectively enrolled in this study between June 2023 and December 2023. All the patients were categorized into intestinal- and diffuse-type groups according to the Lauren classification. Traditional characteristics, including demographic information, serum tumor markers, gastroscopic pathology, and image semantic features, were collected. Spectral quantitative parameters, including iodine concentration (IC), effective atomic number (Zeff), and slope of the energy spectrum curve from 40 keV to 70 keV (λ), were measured three times for each patient by two blinded radiologists in arterial/venous/delayed phases (AP/VP/DP). Differences in traditional features and spectral quantitative parameters between the two groups were compared using univariable analysis. Independent predictors of the Lauren classification of LAGC were screened using multivariable logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminating capability. Ultimately, the nomogram, including clinical features and spectral CT quantitative parameters, was developed. Gender, nIC in AP (APnIC), and λ in DP (λd) were independent predictors for Lauren classification. The nomogram based on these indicators produced the best performance with an area under the curve of 0.841 (95% confidence interval: 0.749-0.932), specificity of 85.3%, accuracy of 76.4%, and sensitivity of 68.4%. The nomogram based on clinical features and spectral CT quantitative parameters exhibits great potential in the preoperative and non-invasive assessment of Lauren classification for LAGC. Question Can the proposed nomogram, integrating clinical features and spectral quantitative parameters, preoperatively predict the Lauren classification in locally advanced gastric cancer (LAGC)? Findings The nomogram, based on gender, arterial phase normalized iodine concentration, and slope of the energy spectrum curve in the delayed phase showed satisfactory predictive ability. Clinical relevance The established nomogram could contribute to guiding individualized treatment strategies and risk stratification in patients by predicting the Lauren classification for LAGC before surgery.

A simple mechanical model of turbulence

This work examines the control and stabilization problems of vibrations in a hierarchical chain of oscillators with hysteresis couplings. Hysteresis coupling is formalized within the Bouc — Wen phenomenological model. The mass, stiffness, and damping properties of the oscillators are set to follow a specific scaling rule and decrease exponentially along the chain, thus forming a hierarchy. The model is verified using Kolmogorov’s hypotheses. To do this, energy spectra are constructed under hysteresis in coupling and without it at different amplitudes of the external excitation. As a result of computational experiments, it is shown that for a chain with hysteresis couplings at a high amplitude of excitation, the energy spectrum curve sufficiently corresponds to Kolmogorov’s hypotheses. The amplitude-frequency characteristics of the system are calculated under hysteresis in coupling using the frequency scanning method. In numerical experiments, frequency ranges of external excitation are identified, which correspond to the chaotic behavior of oscillators and their synchronization.

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small–cell lung cancer

To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC). This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups. Seventy-nine patients aged 60.75±9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC=0.975, 91.5% sensitivity, and 90.6% specificity). The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

Non-electrocardiography-gated dual-energy cardiac CT angiography for assessment of left atrial appendage thrombus

ObjectiveTo explore the diagnosis value of a low dose, dual-energy cardiac computed tomography angiography (CTA) with non-electrocardiography-gated (non-ECG-gated) in detecting left atrial appendage (IAA) thrombus. MethodsConsecutive patients with atrial fibrillation who underwent cardiac CTA protocol (dual-energy scan for arterial phase and conventional scan for delayed phase) were prospectively enrolled. LAA lesions were proved by clinical comprehensive diagnosis, the final study included 18 cases with LAA thrombus and 48 cases with circulatory stasis. Quantitative parameters derived from dual-energy images were measured for the LAA lesions, including the conventional CT attenuation value (CT value), iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number values (Zeff) and energy spectrum curve slope (Slope). The differences between LAA thrombus group and circulatory stasis group were compared by independent sample t-test or Wilcoxon rank sum test regarding to the normality test. The diagnosis performance of the dual-energy parameters was assessed using receiver operating characteristic (ROC) curve analysis and area under curve (AUC). ResultsAll the dual-energy parameters were demonstrated significantly difference between LAA thrombus and circulatory stasis group (P＜0.05), and showed better diagnostic performance than the conventional CT value. ROC analysis revealed IC was the most predictive parameter with AUC equal to 0.836. The radiation dose in the arterial phase was (2.64 ​± ​0.66) mSv. ConclusionDual-energy CTA scanning shows convincing diagnostic performance in detecting left atrial appendage thrombus with lower radiation dose, and may help reduce the need for delayed phase scan.

Diagnostic value of dual-source, dual-energy computed tomography combined with the neutrophil-lymphocyte ratio for discriminating gastric signet ring cell from mixed signet ring cell and non-signet ring cell carcinomas

PurposeTo explore the diagnostic value of dual-source computed tomography (DSCT) and neutrophil to lymphocyte ratio (NLR) for differentiating gastric signet ring cell carcinoma (SRC) from mixed SRC (mSRC) and non-SRC (nSRC).MethodsThis retrospective study included patients with gastric adenocarcinoma who underwent DSCT between August 2019 and June 2021 at our Hospital. The iodine concentration in the venous phase (ICvp), standardized iodine concentration (NICVP), and the slope of the energy spectrum curve (kVP) were extracted from DSCT data. NLR was determined from laboratory results. DSCT (including ICVP, NICVP, and kVP) and combination (including DSCT model and NLR) models were established based on the multinomial logistic regression analysis. The receiver operator characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the diagnostic value.ResultsA total of 155 patients (SRC [n = 45, aged 61.22 ± 11.4 years], mSRC [n = 60, aged 61.09 ± 12.7 years], and nSRC [n = 50, aged 67.66 ± 8.76 years]) were included. There were significant differences in NLR, ICVP, NICVP, and kVP among the SRC, mSRC, and nSRC groups (all P < 0.001). The AUC of the combination model for SRC vs. mSRC + nSRC was 0.964 (95% CI: 0.923-1.000), with a sensitivity of 98.3% and a specificity of 86.7%, higher than with DSCT (AUC: 0.959, 95% CI: 0.919–0.998, sensitivity: 90.0%, specificity: 89.9%) or NLR (AUC: 0.670, 95% CI: 0.577–0.768, sensitivity: 62.2%, specificity: 61.8%).ConclusionDSCT combined with NLR showed high diagnostic efficacy in differentiating SRC from mSRC and nSRC.

The Relationship between Quantitative Parameters of Dual-energy CT and HIF-1α Expression in Non-Small Cell Lung Cancer.

This study aimed to investigate whether there is a correlation between quantitative parameters of dual-energy computed tomography (DECT) and the relative expression of HIF-1&#945; in patients with non-small cell lung cancer (NSCLC) to preliminarily explore the value of DECT in evaluating the hypoxia of tumor microenvironment and tumor biological behavior and provide more information for the treatment of NSCLC. This retrospective research included 36 patients with pathologically confirmed NSCLC who underwent dual-energy enhanced CT scans. The quantitative parameters of DECT were analyzed, including iodine concentration, water concentration, the CT values corresponding to 40keV, 70keV, 100keV, and 130keV in arterial and venous phases, and the normalized iodine concentration and the slope of the energy spectrum curve were calculated. Postoperative specimens underwent HIF immunohistochemical staining by two pathologists. Spearman correlation analysis was adopted as the statistical methodology. The data were analyzed by SPSS26.0 statistical software. Water concentration (r=0.659, P&#60;0.001 and r= 0.632, P&#60;0.001, the CT values corresponding to 100keV (r=0.645, P&#60;0.001 and r= 0.566, P&#60;0.001) and 130keV (r=0.687, P&#60;0.001 and r= 0.682, P&#60;0.001) in arterial and venous phases, and CT value of 70keV in arterial phase (r=0.457, P=0.005) were positively correlated with HIF-1&#945; expression level. There was no correlation among iodine concentration, standardized iodine concentration, CT value of 40keV, λHU, and HIF-1&#945; expression in arterial and venous levels (P >0.05). The quantitative parameters of DECT have a certain correlation with HIF-1&#945; expression in NSCLC. Moreover, it has been demonstrated that DECT can be used to predict hypoxia in tumor tissues and the prognosis of lung cancer patients.

Diagnostic Value of Carotid Plaque Assessment with AIS Based on Quantitative Parameters of Dual-Layer Detector Spectral CT.

To investigate the quantitative assessment of carotid plaque by each parameter of dual-layer detector spectral CT and its diagnostic value in patients with acute cerebral infarction. Eighty-three patients with carotid atherosclerotic plaques who underwent spectral CT scanning were retrospectively included. Forty-two patients with acute ischaemic stroke (AIS) were included in the study group, and 41 patients without AIS were included in the control group. We compared the detection of carotid plaques in the two groups and the differences in the spectral quantitative parameters of the plaques in the two groups, and their diagnostic efficacy was obtained. The detection rate of carotid plaques in the AIS group was higher than that in the non-AIS group (p<0.05); the carotid plaques in the AIS group mainly consisted of non-calcified plaques, while those in the non-AIS group mainly consisted of calcified plaques. The effective atomic number (Zeff), slope of the energy spectrum curve (λH), electron density (ED), and iodine-no-water value of the carotid plaques in the AIS group were lower than those in the non-AIS (p<0.05). For the differentiation of the carotid plaques in the AIS group from those in the non-AIS group, the area under the curve (AUC) of Zeff amounted to 0.637 (cut-off value: 11.865; sensitivity: 72.5%; specificity: 56.2%), the AUC of λH amounted to 0.628 (cut-off value: 19.56; sensitivity: 76.3%; specificity: 51.6%), and that for ED amounted to 0.624 (cut-off value: 110.45; sensitivity: 60.0%; specificity: 64.1%), AUC of iodine-no-water value amounted to 0.645 (cut-off value: 9.125; sensitivity: 61.3%; specificity: 65.6%). In summary, the quantitative parameters of dual-layer detector spectral CT can be used to assess plaque stability and have certain value in the diagnosis of AIS. The quantitative parameters can effectively differentiate carotid plaques in AIS and non-AIS patients.

The Average Sound Energy Spectrum Produced by a Single Raindrop

The characteristics of underwater acoustic radiation generated by a single raindrop impacting the water surface play a fundamental role in the study of rainfall noise. However, the underwater sound signal generated by a single raindrop has great randomness in the amplitude of sound pressure, frequency range and energy size, so that the uncertainty of the sound energy spectrum curve of a single raindrop is relatively large. In this paper, by generating artificial rainfall containing only one size of raindrop, the acoustic radiation generated by artificial rainfall composed of about 136,000 raindrops with an equivalent diameter of 0.9 mm was measured by reverberation method. A smooth, continuous sound energy spectrum of single raindrop covering the full frequency band is obtained.

Mono+ algorithm assessment of the diagnostic value of dual-energy CT for high-risk factors for colorectal cancer: a preliminary study.

Risk factors for colorectal cancer (CRC) affect the way patients are subsequently treated and their prognosis. Dual-energy computerized tomography (DECT) is an advanced imaging technique that enables the quantitative evaluation of lesions. This study aimed to evaluate the quality of DECT images based on the Mono+ algorithm in CRC, and based on this, to assess the value of DECT in the diagnosis of CRC risk factors. This prospective study was performed from 2021 to 2023. A dual-phase DECT protocol was established for consecutive patients with primary CRC. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), overall image quality, lesion delineation, and image noise of the dual-phase DECT images were assessed. Next, the optimal energy-level image was selected to analyze the iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number, electron density, dual-energy index (DEI), and slope of the energy spectrum curve within the tumor for the high- and low-risk CRC groups. A multifactor binary logistic regression analysis was used to construct a differential diagnostic regression model for high- and low-risk CRC, receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to assess the diagnostic value of the model. A total of 74 patients were enrolled in this study, of whom 41 had high-risk factors and 33 had low-risk factors. The SNR and CNR were best at 40 keV virtual monoenergetic imaging (VMI) based on the Mono+ algorithm (VMI+) (SNR 8.79±1.27, P<0.001; CNR 14.89±1.77, P=0.027). The overall image quality and lesion contours were best at 60 keV VMI+ and 40 keV VMI+, respectively (P=0.001). Among all the DECT parameters, the arterial phase (AP)-IC, NIC, DEI, energy spectrum curve, and venous phase-NIC differed significantly between the two groups. The AP-IC was the optimal DECT parameter for predicting high- and low-risk CRC with AUC, sensitivity, specificity, and cut-off values of 0.96, 97.06%, 87.80%, and 2.94, respectively, and the 95% confidence interval (CI) of the AUC was 0.88-0.99. Integrating the clinical factors and DECT parameters, the AUC, sensitivity, specificity, and predictive accuracy of the model were 0.99, 100.00%, 92.68%, and 94.67%, respectively, and the 95% CI of the AUC was 0.93-1.00. The DECT parameters based on 40 keV noise-optimized VMI+ reconstruction images depicted the CRC tumors best, and the clinical DECT model may have significant implications for the preoperative prediction of high-risk factors in CRC patients.

Dual-Energy Computed Tomography Parameters Combined With Inflammatory Indicators Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer.

Cervical lymph node metastasis (CLNM) is considered a marker of papillar Fethicy thyroid cancer (PTC) progression and has a potential impact on the prognosis of PTC. The purpose of this study was to screen for predictors of CLNM in PTC and to construct a predictive model to guide the surgical approach in patients with PTC. This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves. The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively. The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.

Virtual monoenergetic imaging predicting Ki-67 expression in lung cancer

This study aimed to optimize slope and energy levels for evaluating Ki-67 expression in lung cancer using virtual monoenergetic imaging and compare the predictive efficiency of different energy spectrum slopes (λHU) for Ki-67. Forty-three patients with primary lung cancer confirmed via pathological examination were enrolled in this study. They underwent baseline arterial-phase (AP) and venous-phase (VP) energy spectrum computed tomography (CT) scanning before surgery. The CT values were 40–190 keV, with 40–140 keV indicating pulmonary lesions at AP and VP, and P < 0.05 indicating a statistically significant difference. An immunohistochemical examination was conducted, and receiver operating characteristic curves were used to analyze the prediction performance of λHU for Ki-67 expression. SPSS Statistics 22.0 (IBM Corp., NY, USA) was used for statistical analysis, and χ2, t, and Mann–Whitney U tests were used for quantitative and qualitative analyses of data. Significant differences were observed at the corresponding CT values of 40 keV (as 40-keV is considered the best for single-energy image for evaluating Ki-67 expression) and 50 keV in AP and at 40, 60, and 70 keV in VP between high- and low-Ki-67 expression groups (P < 0.05). In addition, the λHU values of three-segment energy spectrum curve in both AP and VP were quite different between two groups (P < 0.05). However, the VP data had greater predictive values for Ki-67. The areas under the curve were 0.859, 0.856, and 0.859, respectively. The 40-keV single-energy sequence was the best single-energy sequence to evaluate the expression of Ki-67 in lung cancer and to obtain λHU values using the energy spectrum curve in the VP. The CT values had better diagnostic efficiency.

Research on Gamma Spectroscopy System While Drilling Based on DSP and FPGA

The traditional gamma energy spectrum measurement system performs filtering, shaping, amplification, baseline recovery, stacking discrimination, peak hold, and low-speed ADC sampling on the pulse signal output by the gamma-ray detector. It generates energy spectrum curves. There are problems such as large dead time and pulse signal accumulation. A high-speed digital processing chip (FPGA) and a high-speed ADC are used to perform full pulse sampling on the amplified ray pulses directly. The high-speed digital processing chip (DSP) directly realizes the pulse signal recognition, which remarkably improves the efficiency of signal acquisition and is very suitable for developing the drill gamma spectroscopy system. Scholars have studied the pulse digital Gaussian shaping algorithm and the trapezoidal shaping algorithm in gamma-spectroscopy while drilling to explore this phenomenon. In this case, a gamma-ray spectrum measurement while drilling system based on DSP and FPGA is designed. It realizes the functions of full-pulse high-speed sampling and energy spectrum curve generation for the narrow pulse signal input to the detector. It also converts the energy spectrum curve. It is transmitted to the host computer through the serial port for energy spectrum analysis.

Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography

ObjectivesTo investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to explore the relationships between DECT and pathological features.MethodsClinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (Zeff) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (λHU), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student’s t-test, Pearson’s rank correlation, and receiver operating characteristic curves were performed.ResultsThe inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (n = 158) displayed significantly decreased ED, IC, normalized IC, λHU, and DEI values compared with non-metastatic nodes (n = 241) (all p < 0.01). Strong correlations were found between IC (r = 0.776), normalized IC (r = 0.779), λHU (r = 0.738), DEI (r = 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918.ConclusionDECT parameters IC, normalized IC, λHU, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC.Key Points• Electron density, iodine concentration, normalized iodine concentration, λHU, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes.• Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density.• DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.

The Effect of CT Imaging Technology in the Diagnosis of Thoracic and Cardiac Surgery Diseases.

In order to increase doctors' cognition of the three-dimensional anatomical structure of cardiothoracic and cardiothoracic surgery and increase the diagnosis rate and cure rate of cardiothoracic surgery diseases, the authors propose a method of CT imaging technology for diagnosing cardiothoracic surgery diseases. Through the joint Hookwire positioning of 3D-CTBA, application in thoracoscopic segmentectomy and CT energy spectrum curve, retrospective analysis of diagnosis of intrathoracic lymph node metastasis in non-small-cell lung cancer, 3D-CTBA and CT-guided Hookwire localization, and preoperative CT-enhanced scanning were performed using two methods. The experimental results showed that the chest tube placement time, postoperative thoracic drainage volume, and postoperative hospital stay after the first operation all showed a good trend. The diagnostic sensitivity was 87.1%. The specificity was 92.6%. The correct index was 79.7%. The accuracy was 91.3%. The positive predictive value was 79.4%. And the negative predictive value was 95.7%. These data prove that CT imaging technology has high diagnostic value for thoracic and cardiac surgery diseases and can effectively help the formulation and implementation of thoracic and cardiac surgery diseases.

Diagnostic value of spiral CT energy spectrum imaging in lymph node metastasis of colorectal cancer.

To evaluate the value of preoperative CT energy spectrum imaging in detecting lymph node metastasis of colorectal cancer. From September 2019 to November 2021, a retrospective study was performed for the eighty-two patients with colorectal cancer through preoperative colonoscopy or surgical pathology confirmed in our hospital. Based on the lymph node metastasis status, these cases were divided into the metastasis and non-metastasis groups. GE Revolution CT scanner was used to scan the patients with energy spectrum imaging, it measured and recorded the single-energy CT values from 40 to 140keV and various energy spectrum parameters of lymph nodes around the lesions in the arterial and venous phases, and statistically analyze the above indices. In the arterial and venous phases: the single-energy CT values of 40-140keV in the non-metastatic group were higher than those in the metastatic group (all P < 0.05); the parameter values of IC (iodine concentration), NIC (normalized iodine concentration), λ (the slope of the energy spectrum curve), and Eff-Z (effective-Z) in the non-metastatic group were higher than those in the metastatic group (all P < 0.05). Further evaluation of ROC curve showed that the higher AUC (area under curve) of the single-energy CT value of 50keV in the arterial phase was 0.889, among the energy spectrum parameters of IC, NIC, λ, and Eff-Z, the NIC had the better diagnostic efficiency and the AUC of the NIC was 0.873, the highest AUC of the combination of NIC and λ was 0.885 when the energy spectrum parameters were combined. The higher AUC of the single-energy CT value of 60keV in the venous phase was 0.853, among the energy spectrum parameters of IC, NIC, λ, and Eff-Z, the λ had the better diagnostic efficiency and the AUC of the λ was 0.822, the higher AUC of the combination of NIC, λ, and Eff-Z was 0.840 when the energy spectra were combined. Parameters of energy spectrum CT imaging can effectively evaluate whether lymph nodes have metastases, and provide favorable imaging diagnosis basis for the range and the number of lymph nodes to be cleaned during clinical operation and can evaluate the prognosis of patients. It is worthy of clinical recommendation.

Noise reduction method of shearer’s cutting sound signal under strong background noise

In coal and rock recognition technology, the acquisition of sound signals is affected by background noise. It is challenging to extract cutting features and accurately identify cutting patterns effectively. Therefore, this paper proposes an approach for combined noise reduction of the cutting sound signal based on the improved adaptive noise complete ensemble empirical mode decomposition (ICEEMDAN) and a singular value decomposition (SVD). First, the method used the ICEEMDAN method to decompose the noisy signal into several intrinsic mode functions (IMF). It calculated the correlation coefficient between the IMF component and the noisy signal and then selected the noisy IMF components based on the threshold formula. Meanwhile, this method constructed a Hankel matrix of the noisy IMF component signals. It used SVD technology to obtain the singular values. According to the singular value standard energy spectrum curve, the paper determined the order of the effective singular value and removed the noise component in the signal. Then, the denoised IMF and noiseless IMF components are superimposed and reconstructed to obtain the noise-reduced cutting sound signal. Finally, it applied simulation signal and simulated shearer cutting experiment to verify the performance of the method. The results show that the proposed method can effectively remove the influence of background noise in the signal and retain the characteristic frequencies of the original cutting sound signal. Compared with traditional noise reduction methods, the ICEEMDAN-SVD combined noise reduction method performs better in noise reduction evaluation standards of signal-noise ratio and root mean square error. It achieved a better noise reduction effect, which could help coal and rock recognition technology based on sound signals.

Reconstruction Algorithm-Based CT Imaging for the Diagnosis of Hepatic Ascites

The study was aimed at exploring the diagnostic value of artificial intelligence reconstruction algorithm combined with CT image parameters on hepatic ascites, expected to provide a reference for the etiological evaluation of clinical abdominal effusion. Specifically, the adaptive iterative hard threshold (AIHT) algorithm for CT image reconstruction was proposed. Then, 100 patients with peritoneal effusion were selected as the research subjects. After 8 cases were excluded, the remaining was divided into 50 cases of the S1 group (hepatic ascites) and 42 cases of the D0 group (cancerous peritoneal effusion). Gemstone energy spectrum CT scanning was performed on all patients, and CT image parameters of the two groups were compared. It was found that CT value of mixed energy, CT value of 60-100 KeV single energy, concentration value of water (calcium), concentration value of water (iodine), and slope of energy spectrum curve in the S1 group were significantly lower than those in the D0 group (P < 0.05). The effective atomic number in the S1 group was significantly higher than that in the D0 group (P < 0.05). Of the 50 patients in the S1 group, 3 (6%) had an ascending and 47 (94%) had a descending spectral curve. Of the 42 patients in the D0 group, 37 (88.1%) had an ascending and 5 (11.9%) had a descending spectral curve. The sensitivity and specificity of water (iodine) were 0.927 and 0.836, respectively. The sensitivity and specificity of water (calcium) were 0.863 and 0.887, respectively. For different scan ranges ([0,90]; [0,120]), root mean square error (RMSE) of AIHT reconstructed image was significantly smaller than that of traditional algorithm, while peak signal-to-noise ratio (PSNR) was opposite. The differences were statistically significant (P < 0.05). In conclusion, AIHT-based CT images can better display the distribution of hepatic ascites, and the parameters of CT value, effective atomic number, water (iodine), water (calcium), and spectral curve can all provide help for the identification of hepatic ascites. Especially, water (iodine) and water (calcium) demonstrated high diagnostic performance of hepatic ascites.

A Nuclide Recognition Method for Nuclear Robot System

In the real energy spectrum attenuation environment, many traditional nuclide identification methods for nuclear robot systems have problems such as using only part of the energy spectrum curve, being susceptible to noise, and having low recognition accuracy. Proposes an energy spectrum nuclide recognition method based on S-transform (ST) and Mahalanobis distance-based support vector machine (MSVM). Regarding the energy spectrum curve as a non-stationary signal, combined with the widely used S transformation method in signal transformation, the energy spectrum data is two-dimensional, Then use two-dimensional principal component analysis(2D-PCA) to reduce the dimension of the two-dimensional energy spectrum data for feature extraction, and design a support vector machine (SVM) classifier based on Mahalanobis distance to realize the identification of energy spectrum nuclides. Finally, experiments are carried out with simulated nuclide energy spectrum data based on Geant4. The experimental results show that this method effectively improves the accuracy of energy spectrum nuclide recognition by using full spectrum information. At the same time, experiments are carried out on the nuclide energy spectrum data of different detection distances obtained by the NaI detector in the real environment, and it is verified that the algorithm proposed in this paper also has a good recognition performance for the nuclide energy spectrum collected in the real environment.

A Preliminary Study on the Feasibility of the Quantitative Parameters of Dual-Energy Computed Tomography Enterography in the Assessment of the Activity of Intestinal Crohn’s Disease

ObjectiveTo investigate the value of dual energy CT enterography (DECTE) in evaluating the activity of Crohn’s disease (CD).MethodsThe endoscopy and imaging data of 29 patients with CD confirmed by clinic and pathology were analyzed retrospectively. The clinical CD activity index (CDAI) was used as the disease activity grouping standard, 29 patients with CD were grouped into activity groups, 18 patients in the active group (CDAI ≥ 150) with 36 intestinal segments, and 11 patients in the remission group (CDAI < 150) with 20 intestinal segments.The virtual single energy CT value, slope of energy spectrum curve and iodine content were analyzed to evaluate the evaluation of intestinal CD activity by DECTE.ResultsThere were statistically significant differences in virtual single energy CT value (except 90 keV and 100 keV virtual single energy CT value), curve slope and iodine content between remission group and active group (P < 0.05), and has more diagnostic value for active phase (AUC > 0.5). ① Virtual single energy CT value: the AUC of 60 keV in arterial phase was the highest (0.924). The specificity of diagnosing CD in active stage was high (95%). ② Curve slope: the AUC of portal vein phase was the largest (0.731). The specificity of diagnosing CD in active stage was higher (85%). ③ Iodine content: the AUC of arterial phase was the highest (0.885). The specificity of diagnosing CD lesions in the active stage was 100%.ConclusionThe virtual single energy CT value, energy spectrum curve slope and iodine content can provide reference for clinical accurate diagnosis of CD activity.

Study on the correlation between energy spectrum computed tomography imaging and the pathological characteristics and prognosis of cervical cancer.

BackgroundThe purpose of this study is to investigate the correlation between energy spectrum computed tomography (CT) imaging and the pathological characteristics and prognosis of cervical cancer.MethodsAll participants underwent energy spectrum CT plain scan and enhanced scan of the cervix, uterine body, and common iliac vein. The correlation between the slope of energy spectrum attenuation curve and pathological characteristics and curative effect was analyzed, and the receiver operating characteristic (ROC) curve of the slope of energy spectrum attenuation curve to distinguish some pathological characteristics and curative effect was constructed.ResultsThe energy spectrum curves of cervix, uterine body, and common iliac vein all showed a downward trend. The slope of cervix energy spectrum curve showed a significant difference in different differentiation degree (P<0.05), and the slope of energy spectrum curve showed an upward trend. The slope of energy spectrum curve of common iliac vein was significantly different between high and low cell proliferation antigen marker (Ki67) (P<0.05), and the slope of Ki67 high expression was higher than that of Ki67 low expression. Treatment was effective in 17 participants and ineffective in 11. After treatment, the energy spectrum curve slope of cervix and energy spectrum curve slope of common iliac vein in the effective group were significantly increased compared with before treatment (P<0.05), and the energy spectrum curve slope of cervix in the ineffective group was increased compared with before treatment, but the difference was not significant (P>0.05). The area under the curve (AUC) of distinguishing Ki67 expression of energy spectrum curve slope of common iliac vein was 0.7008, sensitivity was 66.67%, and specificity was 62.34%. The AUC of distinguishing the curative effect of cervical energy spectrum curve slope was 0.6131, sensitivity was 56.25%, and specificity was 59.09%. The AUC of distinguishing the curative effect of energy spectrum curve slope of common iliac vein was 0.6563, sensitivity was 60.42%, and specificity was 58.33%.ConclusionsThe energy spectrum curve slope has potential value in the prediction of certain specific pathological types of cervical cancer and the evaluation of curative effect.