scholarly journals Artificial Intelligence Algorithm-Based Computed Tomography Images in the Evaluation of the Curative Effect of Enteral Nutrition after Neonatal High Intestinal Obstruction Operation

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yanqing Dong ◽  
Zhaolong Wang ◽  
Zhiguang Zhang ◽  
Bobo Niu ◽  
Pan Chen ◽  
...  
Keyword(s):  
Enteral Nutrition ◽  
Intestinal Obstruction ◽  
Level Set ◽  
Segmentation Algorithm ◽  
Control Group ◽  
Observation Group ◽  
Ct Image ◽  
Level Set Segmentation ◽  
Traditional Algorithm ◽  
High Intestinal Obstruction

In this study, CT image technology based on level set intelligent segmentation algorithm was used to evaluate the postoperative enteral nutrition of neonatal high intestinal obstruction and analyze the clinical treatment effect of high intestinal obstruction, so as to provide a reasonable research basis for the clinical application of neonatal high intestinal obstruction. 60 children with high intestinal obstruction treated in the hospital were selected as the research objects. Based on the postoperative enteral nutrition treatment, they were divided into control group (noncatheterization group)-parenteral nutrition support. In the observation group, gastric tube was placed through nose for nutritional support. Then, CT images based on level set segmentation algorithm were used to compare the intestinal recovery of the two groups, and the biochemical indexes and hospitalization were compared. The level set algorithm can accurately segment the lesions in CT images. The segmentation time of the level set algorithm was shorter than that of the traditional algorithm (24.34 ± 2.01 s vs. 75.21 ± 5.91 s), and the segmentation accuracy was higher than that of the traditional algorithm (84.71 ± 3.91% vs. 70.04 ± 3.71%, P  < 0.05). The weight of children in the observation group (100 ± 7 g) was higher than that in the control group (54 ± 5 g), and the ICU monitoring time (12.01 ± 2.65 days) and the hospital stay (17.82 ± 3.11 days) were shorter than those in the control group (13.42 ± 2.95 days, 19.13 ± 3.22 days, all P  < 0.05). The level set segmentation algorithm can accurately segment the CT image, so that the disease location and its contour can be displayed more clearly. Moreover, the nasal placement of jejunal nutrition tube can effectively improve the intestinal function of children, maintain the steady-state environment of intestinal bacterial growth, and significantly improve the clinical treatment effect, which is worthy of clinical application and promotion.

scholarly journals Intelligent Algorithm-Based Computed Tomography Image Features in Diagnosis of the Effect of Radiofrequency Ablation in Liver Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yufeng Cha ◽  
Zhili Wei ◽  
Chi Ma ◽  
Lei Zhang
Keyword(s):  
Computed Tomography ◽  
Radiofrequency Ablation ◽  
Ct Images ◽  
Segmentation Algorithm ◽  
Control Group ◽  
Observation Group ◽  
Ct Image ◽  
Comprehensive Diagnosis ◽  
Kappa Value ◽  
The Difference

To provide a reference for finding a reasonable evaluation method for treatment effect of radiofrequency ablation (RFA), computed tomography (CT) image optimized by the intelligent segmentation algorithm was utilized to evaluate the liver condition of hepatocellular carcinoma (HCC) patients after RFA and to estimate the patient’s prognosis. Eighty-eight patients with HCC who needed RFA surgery after diagnosis in our hospital were selected. The CT images before optimization were set as the control group; the CT images after optimization were set as the observation group. Comprehensive diagnosis was taken as the gold standard to compare the ablation range and residual lesions under CT scans before and after surgery. The results showed that the consistency of the two sets of CT images was compared with comprehensive diagnosis under different diameters of the lesion. The difference between the two groups was not statistically considerable when the diameter of the lesion was less than 50 mm ( P > 0.05 ). For lesions larger than 50 mm in diameter, the consistency of the observation group (83%) was remarkably higher than that of the control group (40%), and the difference was substantial ( P < 0.05 ). The kappa value of the observation group was 0.84 and that of the control group was 0.78. The kappa value of observation group was better than the control group, with considerable difference ( P < 0.05 ). In conclusion, the diagnostic effect of CT image based on intelligent segmentation algorithm was superior to conventional diagnosis when the diameter of the lesion was larger than 50 mm. Moreover, the overall improvement rate of patients after RFA treatment was far greater than the recurrence rate, indicating that the clinical adoption of RFA was very meaningful.

Retraction Notice: Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images

2018 ◽  
Vol 14 ◽  
Author(s):  
G. Elaiyaraja
Keyword(s):  
Medical Imaging ◽  
Level Set ◽  
Current Medical ◽  
Segmentation Algorithm ◽  
Scientific Publishing ◽  
Swarm Optimization ◽  
Original Source ◽  
Level Set Segmentation ◽  
Copyright Violation ◽  
Retraction Notice

The article entitled “Improved Level Set Segmentation Algorithm Based on Kernel Fuzzy Particles Swarm Optimization (KFPSO) Clustering for MRI Images”, by G. Elaiyaraja, P. Epsiba, N. Kumaratharan and G. Suresh, has been retracted. Kindly see Bentham Science Policy on Article retraction at the link given below: (https://www.benthamscience.com/journals/current-medical-imaging/author-guidelines/). This article has been retracted on the request of the Editor. The authors have plagiarized a paper that had already been published in the journal Current Medical Imaging (CMIM) (Formerly: Current Medical Imaging Reviews) 14(3), Page: 389-400. http://www.eurekaselect.com/149444. It is a pre-requisite for authors to declare explicitly that their work is original and has not been published elsewhere. Authors are advised to properly cite the original source to avoid plagiarism and copyright violation. As such this article represents a severe abuse of the scientific publishing system. Bentham Science Publishers takes a very strong view on this matter and apologizes to the readers of the journal for any inconvenience this may cause.

scholarly journals CT Image Features of the FBP Reconstruction Algorithm in the Evaluation of Fasting Blood Sugar Level of Diabetic Pulmonary Tuberculosis Patients and Early Diet Nursing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lili Hong ◽  
Liling Lin ◽  
Jingping Chen ◽  
Biyu Wu
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Clinical Symptoms ◽  
Fasting Glucose ◽  
Reconstruction Algorithm ◽  
Control Group ◽  
Observation Group ◽  
Ct Image ◽  
Glucose Levels ◽  
Patients With Diabetes

The study was aimed at exploring the application value of the CT image based on a filtered back projection (FBP) algorithm in the diagnosis of patients with diabetes complicated with tuberculosis and at analyzing the influence of dietary nursing on patients with diabetes complicated with tuberculosis. In this study, the FBP algorithm was used to optimize CT images to effectively obtain reconstructed ROI images. Then, the deviation from measurement values of reconstructed images at different pixel levels was analyzed. 138 patients with diabetes complicated with tuberculosis were selected as research subjects to compare the number of lung segments involved and the CT imaging manifestations at different fasting glucose levels. All patients were divided into the control group (routine drug treatment) and observation group (diet intervention on the basis of drug treatment) by random number table method, and the effect of different nursing methods on the improvement of patients’ clinical symptoms was discussed. The results showed that the distance measurement value decreased with the increase in pixel level, there was no significant difference in the number of lung segments involved in patients with different fasting glucose levels ( P > 0.05 ), and there were statistically significant differences in the incidence of segmental lobar shadow, bronchial air sign, wall-less cavity, thick-walled cavity, pulmonary multiple cavity, and bronchial tuberculosis in patients with different fasting glucose levels ( P < 0.05 ). Compared with the control group, 2 h postprandial blood glucose level in the observation group was significantly improved ( P < 0.05 ), there was a statistical significance in the number with reduced pleural effusion and the number with reduced tuberculosis foci in the two groups ( P < 0.05 ), and the level of hemoglobin in the observation group was 7.1 ± 1.26 , significantly lower than that in the control group ( 8.91 ± 2.03 , P < 0.05 ). It suggested that the changes of CT images based on the FBP reconstruction algorithm were correlated with fasting blood glucose level. Personalized diet nursing intervention can improve the clinical symptoms of patients, which provides a reference for the clinical diagnosis and treatment of patients with diabetes complicated with tuberculosis.

scholarly journals ABLE: An Activity-Based Level Set Segmentation Algorithm for Two-Photon Calcium Imaging Data

eNeuro ◽  
2017 ◽  
Vol 4 (5) ◽  
pp. ENEURO.0012-17.2017 ◽  
Author(s):  
Stephanie Reynolds ◽  
Therese Abrahamsson ◽  
Renaud Schuck ◽  
P. Jesper Sjöström ◽  
Simon R. Schultz ◽  
...  
Keyword(s):  
Level Set ◽  
Calcium Imaging ◽  
Segmentation Algorithm ◽  
Imaging Data ◽  
Two Photon ◽  
Level Set Segmentation

scholarly journals Effect of family nutrition therapy on elderly patients with chronic obstructive pulmonary disease

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Jun Xue ◽  
Yanan Zhang ◽  
Zhaohe Song ◽  
Lei Wang ◽  
Baoyin Bo
Keyword(s):  
Quality Of Life ◽  
Enteral Nutrition ◽  
Elderly Patients ◽  
Nutrition Support ◽  
Control Group ◽  
Chronic Obstructive ◽  
Observation Group ◽  
Obstructive Pulmonary Disease ◽  
Enteral Nutrition Support

Aims:Objective to explore the influence of family enteral nutrition support on nutritional status, lung function, activity tolerance and quality of life in elderly patients with chronic obstructive pulmonary disease (COPD) in stable stage and malnutrition. Methods: a total of 165 elderly patients with COPD and malnutrition discharged from the geriatric department of our hospital were randomly divided into two groups: control group (82 cases) and observation group (83 cases). The control group was treated with conventional diet, and the observation group was treated with conventional diet + enteral nutrition suspension (nengjin, 500kcal / bottle, newdisia Pharmaceutical Co., Ltd.) for support. One month later, they were observed The body mass index (BMI), serum albumin (ALB), total protein (TP), hemoglobin (HB), pulmonary function of the two groups were observed: forced vital capacity (FVC), forced expiratory volume (FEV1) in the first second, FEV1 / FVC, FEV1% of the predicted value (FEV1%), exercise tolerance and quality of life.Results (1) compared with the control group, BMI and ALB in the observation group increased significantly (t = 10.465, 6.189, P < 0.05), TP and Hb had no significant change, and the difference was not statistically significant (t = 1.310, 1.302, P > 0.05). (2) compared with the control group, FVC, FEV1, FEV1 / FVC, FEV1% in the observation group increased, with statistical differences (t = 11.999, 19.654, 13.418, 16.924, P < 0.05). (3) compared with the control group, the quality of life symptom score, activity score, influence score and total score of the observation group decreased significantly (t = 15.303, 6.773, 23.600, 14.766, P < 0.05), and 6MWT increased significantly (t = 111.962, P < 0.05).Conclusion enteral nutrition support can improve the nutritional status, lung function, activity tolerance and quality of life of elderly patients with COPD in stable stage and malnutrition.

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