scholarly journals Multispectral Image under Tissue Classification Algorithm in Screening of Cervical Cancer

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Pei Wang ◽  
Shuwei Wang ◽  
Yuan Zhang ◽  
Xiaoyan Duan
Keyword(s):  
Cervical Cancer ◽  
Clinical Application ◽  
Sensitivity And Specificity ◽  
Statistical Difference ◽  
Multispectral Imaging ◽  
Classification Algorithm ◽  
Multispectral Image ◽  
Multispectral Images ◽  
Tissue Classification ◽  
The Difference

The objectives of this study were to improve the efficiency and accuracy of early clinical diagnosis of cervical cancer and to explore the application of tissue classification algorithm combined with multispectral imaging in screening of cervical cancer. 50 patients with suspected cervical cancer were selected. Firstly, the multispectral imaging technology was used to collect the multispectral images of the cervical tissues of 50 patients under the conventional white light waveband, the narrowband green light waveband, and the narrowband blue light waveband. Secondly, the collected multispectral images were fused, and then the tissue classification algorithm was used to segment the diseased area according to the difference between the cervical tissues without lesions and the cervical tissues with lesions. The difference in the contrast and other characteristics of the multiband spectrum fusion image would segment the diseased area, which was compared with the results of the disease examination. The average gradient, standard deviation (SD), and image entropy were adopted to evaluate the image quality, and the sensitivity and specificity were selected to evaluate the clinical application value of discussed method. The fused spectral image was compared with the image without lesions, it was found that there was a clear difference, and the fused multispectral image showed a contrast of 0.7549, which was also higher than that before fusion (0.4716), showing statistical difference ( P < 0.05 ). The average gradient, SD, and image entropy of the multispectral image assisted by the tissue classification algorithm were 2.0765, 65.2579, and 4.974, respectively, showing statistical difference ( P < 0.05 ). Compared with the three reported indicators, the values of the algorithm in this study were higher. The sensitivity and specificity of the multispectral image with the tissue classification algorithm were 85.3% and 70.8%, respectively, which were both greater than those of the image without the algorithm. It showed that the multispectral image assisted by tissue classification algorithm can effectively screen the cervical cancer and can quickly, efficiently, and safely segment the cervical tissue from the lesion area and the nonlesion area. The segmentation result was the same as that of the doctor's disease examination, indicating that it showed high clinical application value. This provided an effective reference for the clinical application of multispectral imaging technology assisted by tissue classification algorithm in the early screening and diagnosis of cervical cancer.

scholarly journals Spectral–Spatial Feature Partitioned Extraction Based on CNN for Multispectral Image Compression

2020 ◽  
Vol 13 (1) ◽  
pp. 9
Author(s):  
Fanqiang Kong ◽  
Kedi Hu ◽  
Yunsong Li ◽  
Dan Li ◽  
Shunmin Zhao
Keyword(s):  
Feature Extraction ◽  
Image Compression ◽  
Multispectral Imaging ◽  
Rapid Development ◽  
Spectral Feature ◽  
Multispectral Image ◽  
Landsat 8 ◽  
Spatial Feature ◽  
Spatial Features ◽  
Multispectral Image Compression

Recently, the rapid development of multispectral imaging technology has received great attention from many fields, which inevitably involves the image transmission and storage problem. To solve this issue, a novel end-to-end multispectral image compression method based on spectral–spatial feature partitioned extraction is proposed. The whole multispectral image compression framework is based on a convolutional neural network (CNN), whose innovation lies in the feature extraction module that is divided into two parallel parts, one is for spectral and the other is for spatial. Firstly, the spectral feature extraction module is used to extract spectral features independently, and the spatial feature extraction module is operated to obtain the separated spatial features. After feature extraction, the spectral and spatial features are fused element-by-element, followed by downsampling, which can reduce the size of the feature maps. Then, the data are converted to bit-stream through quantization and lossless entropy encoding. To make the data more compact, a rate-distortion optimizer is added to the network. The decoder is a relatively inverse process of the encoder. For comparison, the proposed method is tested along with JPEG2000, 3D-SPIHT and ResConv, another CNN-based algorithm on datasets from Landsat-8 and WorldView-3 satellites. The result shows the proposed algorithm outperforms other methods at the same bit rate.

scholarly journals Raman spectroscopic study of cervical precancerous lesions and cervical cancer

2021 ◽  
Author(s):  
Jing Wang ◽  
Cheng-Xia Zheng ◽  
Cai-Ling Ma ◽  
Xiang-Xiang Zheng ◽  
Xiao-Yi Lv ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Squamous Cell Carcinoma ◽  
Raman Spectra ◽  
Precancerous Lesions ◽  
Cervical Squamous Cell Carcinoma ◽  
Cervical Lesions ◽  
Cin Iii ◽  
Cervical Precancerous Lesions ◽  
Biochemical Components ◽  
The Difference

AbstractEarly detection of cervical lesions, accurate diagnosis of cervical lesions, and timely and effective therapy can effectively avoid the occurrence of cervical cancer or improve the survival rate of patients. In this paper, the spectra of tissue sections of cervical inflammation (n = 60), CIN (cervical intraepithelial neoplasia) I (n = 30), CIN II (n = 30), CIN III (n = 30), cervical squamous cell carcinoma (n = 30), and cervical adenocarcinoma (n = 30) were collected by a confocal Raman micro-spectrometer (LabRAM HR Evolution, Horiba France SAS, Villeneuve d’Ascq, France). The Raman spectra of six kinds of cervical tissues were analyzed, the dominant Raman peaks of different kinds of tissues were summarized, and the differences in chemical composition between the six tissue samples were compared. An independent sample t test (p ≤ 0.05) was used to analyze the difference of average relative intensity of Raman spectra of six types of cervical tissues. The difference of relative intensity of Raman spectra of six kinds of tissues can reflect the difference of biochemical components in six kinds of tissues and the characteristic of biochemical components in different kinds of tissues. The classification models of cervical inflammation, CIN I, CIN II, CIN III, cervical squamous cell carcinoma, and cervical adenocarcinoma were established by using a support vector machine (SVM) algorithm. Six types of cervical tissues were classified and identified with an overall diagnostic accuracy of 85.7%. This study laid a foundation for the application of Raman spectroscopy in the clinical diagnosis of cervical precancerous lesions and cervical cancer.

scholarly journals A multispectral 3D-Endoscope for Cholesteatoma Removal

2020 ◽  
Vol 6 (3) ◽  
pp. 257-260
Author(s):  
Eric L. Wisotzky ◽  
Jean-Claude Rosenthal ◽  
Anna Hilsmann ◽  
Peter Eisert ◽  
Florian C. Uecker
Keyword(s):  
Multispectral Imaging ◽  
Narrow Band ◽  
Tissue Classification ◽  
Step Size ◽  
3D Endoscope ◽  
Before And After ◽  
Overlay Technique ◽  
Ct Data ◽  
Metric Dimensions ◽  
20 Nm

AbstractWe present a stereo-multispectral endoscopic prototype using a filter-wheel to guide the removal of cholesteatoma tissue in the middle ear. An image-based method is used that combines multispectral tissue classification for the detection of tissue to be removed and 3Dreconstruction to determine its metric dimensions. The multispectral illumination used for tissue classification ranges from λ = 400 nm to λ = 500 nm with step-size of 20 nm, which results in six different narrow-band illumination modes. For classical RGB imaging and metric calculations, a broadband illumination mode is applied before and after the narrow-band illumination. The spectral information is augmented into the broadband mode using an overlay technique. The combination of multispectral imaging with stereoscopic 3D-reconstruction results in new valuable visualization of intraoperative data. This allows to generate a 3D-model of the patients anatomy highlighting the identified malicious tissue and compare the anatomical dimensions with pre-operative CT data.

Association Between the CDC6 G1321A Polymorphism and the Risk of Cervical Cancer

2010 ◽  
Vol 20 (5) ◽  
pp. 856-861 ◽  
Author(s):  
Xing-Dong Xiong ◽  
Li-Qin Zeng ◽  
Qing-Yuan Xiong ◽  
Sheng-Xiang Lu ◽  
Zhi-Zhen Zhang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cell Proliferation ◽  
Statistical Significance ◽  
Biological Significance ◽  
Brdu Incorporation ◽  
General Validity ◽  
Cervical Cancer Risk ◽  
Healthy Female ◽  
The Difference ◽  
Incorporation Assay

Introduction:Cell division cycle protein 6 (CDC6) plays critical roles in DNA replication and carcinogenesis. The biological significance of the CDC6 G1321A polymorphism (V441I, rs13706) on cervical carcinogenesis is still unknown. Here, we examined the potential influence of this polymorphism on cell proliferation and the individual's susceptibility to cervical cancer.Methods:We genotyped the CDC6 G1321A polymorphism in 87 cervical cancer cases and 110 healthy female subjects. Unconditional logistic regression analysis was used to estimate the association between the genotypes and the risk of cervical cancer. The BrdU incorporation assay was applied to analyze the effect of this polymorphism on cell proliferation.Results:Compared with the GG homozygotes, the cervical cancer risk was significantly reduced in the individuals with the heterozygous AG genotype (odds ratio [OR], 0.53; 95% confidence interval [CI], 0.28-0.98; P = 0.042) or the homozygous AA genotype (OR, 0.29; 95% CI, 0.09-0.89; P = 0.030). Further stratified analyses showed that the decreased risk of cervical cancer was more evident among younger subjects (≤44 years old) with the AG or AA genotypes (OR, 0.44; 95% CI, 0.21-0.92; P = 0.029 and OR, 0.12; 95% CI, 0.03-0.61; P = 0.010, respectively). The BrdU incorporation assay showed that 293T cells transfected with CDC6-441I (1321A) had a lower proliferation rate in comparison with those transfected with CDC6-441V (1321G), although the difference did not reach statistical significance at the 0.05 level.Conclusions:The CDC6 G1321A polymorphism may contribute to the risk of cervical cancer. Further studies with more subjects and in diverse ethnic populations are necessary to confirm the general validity of our findings.

scholarly journals Comparison of Effectiveness and Patient Satisfaction of Vaginal Versus Oral Misoprostol in Treatment of Missed Miscarriage

2019 ◽  
Vol 7 (6) ◽  
pp. 955-958 ◽  
Author(s):  
Elham Mohammadi ◽  
Geetha Jayaprakash ◽  
Afshin Shiva ◽  
Nader Motallebzadeh
Keyword(s):  
Patient Satisfaction ◽  
Statistical Difference ◽  
Missed Abortion ◽  
Patient’S Satisfaction ◽  
Patients Satisfaction ◽  
Satisfaction Rate ◽  
Oral Misoprostol ◽  
Surgical Evacuation ◽  
The Difference ◽  
Vaginal Misoprostol

BACKGROUND: In recent years’ medical management with misoprostol is an effective alternative to surgical evacuation. But there is a dearth of evidence to reveal the effectiveness of the different routes of misoprostol and satisfaction rate among the patients treated with these routes. AIM: This study was conducted to compare the effectiveness and patient’s satisfaction rate of vaginal versus oral misoprostol. METHODS: It was a prospective non-interventional study. One hundred women of having missed abortion confirmed by ultrasonography examination were enrolled in the trial. Fifty-eight subjects were administered 200 mcg of oral and 42 subjects received 200 mcg of vaginal misoprostol every four hours up to four doses. If complete expulsion did not occur 12 hours after the last dose, the surgical evacuation was done. RESULTS: There was no significant statistical difference between the effectiveness of treatment with vaginal (78.57%) and oral misoprostol (79.31%) (p = 0.928). The difference between Patients’ satisfaction at the time of discharge for the vaginal group (64.29%) and oral group (65.52%) was not statistically significant (P = 0.991). There was an increase in patients’ satisfaction for both groups at the follow-up session, but still, the difference was not significant (P = 0.897). CONCLUSION: This study confirms that there is no statistical difference between the effectiveness and patient satisfaction of oral and vaginal misoprostol in the treatment of missed abortion.

scholarly journals Comparison of the sensitivity and specificity of real-time PCR and in situ hybridization in HPV16 and 18 detection in archival cervical cancer specimens

2012 ◽  
Vol 50 (2) ◽  
pp. 239-247 ◽  
Author(s):  
Beata Biesaga ◽  
Sława Szostek ◽  
Małgorzata Klimek ◽  
Jerzy Jakubowicz ◽  
Joanna Wysocka
Keyword(s):  
Cervical Cancer ◽  
Real Time ◽  
Sensitivity And Specificity ◽  
Real Time Pcr

scholarly journals A Contemporary Machine Learning Method for Accurate Prediction of Cervical Cancer

2021 ◽  
Vol 102 ◽  
pp. 04004
Author(s):  
Jesse Jeremiah Tanimu ◽  
Mohamed Hamada ◽  
Mohammed Hassan ◽  
Saratu Yusuf Ilu
Keyword(s):  
Machine Learning ◽  
Cervical Cancer ◽  
Feature Selection ◽  
Decision Tree ◽  
Sensitivity And Specificity ◽  
Missing Values ◽  
New Technologies ◽  
Machine Learning Techniques ◽  
Screening Tests ◽  
Tree Classifier

With the advent of new technologies in the medical field, huge amounts of cancerous data have been collected and are readily accessible to the medical research community. Over the years, researchers have employed advanced data mining and machine learning techniques to develop better models that can analyze datasets to extract the conceived patterns, ideas, and hidden knowledge. The mined information can be used as a support in decision making for diagnostic processes. These techniques, while being able to predict future outcomes of certain diseases effectively, can discover and identify patterns and relationships between them from complex datasets. In this research, a predictive model for predicting the outcome of patients’ cervical cancer results has been developed, given risk patterns from individual medical records and preliminary screening tests. This work presents a Decision tree (DT) classification algorithm and shows the advantage of feature selection approaches in the prediction of cervical cancer using recursive feature elimination technique for dimensionality reduction for improving the accuracy, sensitivity, and specificity of the model. The dataset employed here suffers from missing values and is highly imbalanced. Therefore, a combination of under and oversampling techniques called SMOTETomek was employed. A comparative analysis of the proposed model has been performed to show the effectiveness of feature selection and class imbalance based on the classifier’s accuracy, sensitivity, and specificity. The DT with the selected features and SMOTETomek has better results with an accuracy of 98%, sensitivity of 100%, and specificity of 97%. Decision Tree classifier is shown to have excellent performance in handling classification assignment when the features are reduced, and the problem of imbalance class is addressed.

scholarly journals Pendugaan Intensitas Serangan Penyakit BLB (Bacterial Leaf Blight) pada Tanaman Padi melalui Pendekatan Citra Multispektral

2020 ◽  
Vol 8 (2) ◽  
pp. 338
Author(s):  
Gusti Bagus Eka Chandra ◽  
I Made Anom S. Wijaya ◽  
Yohanes Setiyo
Keyword(s):  
Technology Development ◽  
Leaf Blight ◽  
Multispectral Image ◽  
Bacterial Leaf Blight ◽  
Estimation Accuracy ◽  
Multispectral Images ◽  
Multispectral Imagery ◽  
Rice Plants ◽  
Red Edge ◽  
Disease Attack

ABSTRAK Penyakit Bacterial Leaf Blight (BLB) merupakan salah satu penyakit yang berbahaya bagi tanaman padi. Penyakit ini bisa menyerang di setiap fase pertumbuhan. Perhitungan intensitas serangan penyakit BLB saat ini masih dilakukan secara manual. Diperlukan pengembangan teknologi dalam pendugaan intensitas serangan penyakit BLB melalui citra multispektral. Penelitian ini bertujuan untuk (1) untuk mendapatkan nilai korelasi terbaik antara intensitas serangan penyakit BLB dengan parameter citra multispektral (2) Untuk mendapatkan persamaan pendugaan intensitas serangan penyakit BLB berdasarkan pendekatan citra multispektral. Drone DJI Inspire 1 dengan kamera multispektral digunakan untuk menangkap gambar petak padi. Pengolahan data citra multispektral menggunakan Agisoft Photoscan dan software QGIS 3.8. Berdasarkan dari hasil akuisisi, citra multispektral menghasilkan citra band red, NIR, green, red edge, RGB yang kemudian diolah menjadi transformasi citra NDVI, EVI, dan NDRE. Dari ketiga parameter citra multispektral, nilai NDVI memiliki tingkat korelasi yang lebih kuat dengan koefisien determinasi sebesar 97,5% dan menghasilkan persamaan linier sebagai berikut y = -419,6 + 169,3. Dalam perhitungan nilai eror parameter NDVI memilikinilai eror paling rendah dibandingkan parameter EVI dan NDRE yaitu sebesar 4,64% dengan akurasi pendugaan 95,36%. Citra multispektral dapat digunakan dalam pendugaan intensitas serangan penyakit BLB pada tanaman padi karena menghasilkan nilai korelasi yang sangat kuat, dan akurasi pendugaan yang tinggi dengan nilai eror yang rendah tidak melebihi 10%. ABSTRACT  Bacterial Leaf Blight (BLB) is a disease that is dangerous for rice plants. This disease can attack in every phase of growth. Calculation of BLB disease attack intensity is currently still used manually method. Technology development is needed in estimating the intensity of BLB disease through multispectral imagery. This study aims (1) to get the best correlation value between the intensity of BLB disease attack with multispectral image parameters (2) to get the equation for estimating the intensity of BLB based on multispectral images parameter. Drone DJI Inspire 1 with a multispectral camera is used to captured the paddy field. The captured images was processed using Agisoft Photoscan and QGIS 3.8 software. Based on the results of the acquisition, multispectral images produce red, NIR, green, red edge, RGB band images which were then transformed into NDVI, EVI, and NDRE images. Of the three multispectral image parameters, NDVI values ??have a stronger correlation level with a determination coefficient of 97.5% and produce the following linear equation y = -419.6 + 169.3. In calculating the NDVI parameter error value has the lowest error value compared to the EVI and NDRE parameters which is 4.64% with an accuracy estimate of 95.36%. Multispectral imagery can be used in estimating the intensity of BLB disease attacks in rice plants because it produces a very strong correlation value, and high estimation accuracy with a low error value does not exceed 10%.

scholarly journals Analysis of the Effect of Three - Row Nail in Gastric Cancer Operation

1970 ◽  
Vol 1 (1) ◽  
Author(s):  
Wang Guang yong
Keyword(s):  
Gastric Cancer ◽  
Methylene Blue ◽  
Clinical Application ◽  
Skin Flap ◽  
Control Group ◽  
Observation Group ◽  
External Reinforcement ◽  
Methylene Blue Test ◽  
The Difference ◽  
Observational Group

To study on the clinical efficacy of the repairing of the toe defect of the tip of the toe artery with skin flap. 48 patients with tip of toe defects who were admitted to our department from May 2014 to December 2015 were randomly divided into two groups: control group and observation group, 24 cases in each group. The patients in the control group were treated with abdominal pedicle flap while the patients in the observation group were treated with the toe artery skin flap for repair. The clinical curative effect of the two groups was analyzed. The total effective rate of clinical treatment was 23 (95.83%) in the observation group was significantly higher than that in the control group, 19 (79.16%), and the elasticity and texture of the flap were good and no obvious adverse reaction occurred. The difference between the two groups was significant, p<0.05. The use of the toe artery skin flap for the treatment of the tip of toe defect has a significant clinical effect, and no serious adverse reactions occurred, highly safety.15To explore the clinical application of three-row stapler in the operation of gastric cancer, and to provide a reference for clinical application. 31 patients with gastric cancer from January 2015 to April 2017 were randomly divided into observational group and control group. The observational group (n = 16) received three rows of the stapler; the control group (n = 15) received two rows of the stapler. The general condition, complication and anastomotic condition of the two groups were recorded, and the occurrence of anastomotic leakage was tested by methylene blue test. There was no significant difference in the operation time between the two groups ( P> 0.05). The length of stay in the hospital for the observational group was (16.17 ± 5.25) d, which was significantly lower than that of the control group (22.35 ± 7.18) d, the difference was statistically significant (P < 0.05). The incidence of complications was 7.14%, which was significantly lower than that of the control group (26.67%, P < 0.05). The number of bleeding in the anastomosis of the observational group was (0.87 ± 0.61), and the number of the outermost anastomosis was 0.95 ± 0.49, which was significantly lower than that of the control group (P<0.01). In the observational group, only one case (6.28%) was positive in the methylene blue test, which was significantly lower than that in the control group (20%) (P < 0.05). Three-row stapler can be used to treat the traditional two-row nail stapler, and no external reinforcement is needed after anastomosis. At the same time, it can effectively control the anastomotic bleeding, outer ring nail exposure and anastomotic leakage complications occur and clinical hospital stays shorter, more efficient treatment, worthy of clinical application.

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