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Multimodality Medical Image Fusion Based on Pixel Significance with Edge-Preserving Processing for Clinical Applications

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Computers, Materials & Continua 2024年第3期78卷 4317-4342页

作者： Bhawna Goyal Ayush dogra Dawa Chyophel Lepcha Rajesh Singh Hemant Sharma Ahmed Alkhayyat Manob Jyoti Saikia Department of ECE and UCRD Chandigarh UniversityMohaliPunjab140413India Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India Department of ECE Uttaranchal Institute of TechnologyUttaranchal UniversityDehradun248007India IES College of Technology IES UniversityBhopal462044India College of Technical Engineering The Islamic UniversityNajaf54001Iraq Department of Electrical Engineering University of North FloridaJacksonvilleFL32224USA

Multimodal medical image fusion has attained immense popularity in recent years due to its robust technology for clinical diagnosis.It fuses multiple images into a single image to improve the quality of images by retaining significant information and aiding diagnostic practitioners in diagnosing and treating many diseases.However,recent image fusion techniques have encountered several challenges,including fusion artifacts,algorithm complexity,and high computing costs.To solve these problems,this study presents a novel medical image fusion strategy by combining the benefits of pixel significance with edge-preserving processing to achieve the best fusion performance.First,the method employs a cross-bilateral filter(CBF)that utilizes one image to determine the kernel and the other for filtering,and vice versa,by considering both geometric closeness and the gray-level similarities of neighboring pixels of the images without smoothing edges.The outputs of CBF are then subtracted from the original images to obtain detailed images.It further proposes to use edge-preserving processing that combines linear lowpass filtering with a non-linear technique that enables the selection of relevant regions in detailed images while maintaining structural properties.These regions are selected using morphologically processed linear filter residuals to identify the significant regions with high-amplitude edges and adequate size.The outputs of low-pass filtering are fused with meaningfully restored regions to reconstruct the original shape of the edges.In addition,weight computations are performed using these reconstructed images,and these weights are then fused with the original input images to produce a final fusion result by estimating the strength of horizontal and vertical details.Numerous standard quality evaluation metrics with complementary properties are used for comparison with existing,well-known algorithms objectively to validate the fusion results.Experimental results from the proposed research article exhibit superior per

关键词： Image fusion fractal data analysis biomedical diseases research multiresolution analysis numerical analysis

EXECUTER2 modulates the EXECUTER1 signalosome through its singlet oxygen-dependent oxidation

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Molecular Plant 2022年第3期15卷 438-453页

作者： Vivek dogra Rahul Mohan Singh Mengping Li Mingyue Li Somesh Singh Chanhong Kim Shanghai Center for Plant Stress Biology CAS Center for Excellence in Molecular Plant SciencesChinese Academy of SciencesShanghai 200032China University of the Chinese Academy of Sciences Beijing 100049China Present address:Biotechnology Division CSIR-Institute of Himalayan Bioresource TechnologyPalampur 176061India

Oxidative post-translational modifications of specific chloroplast proteins contribute to the initiation of retrograde signaling.The Arabidopsis thaliana EXECUTER1(EX1)protein,a chloroplast-localized singlet oxygen(^(1)O_(2))sensor,undergoes tryptophan(Trp)643 oxidation by^(1)O_(2),a chloroplast-derived and light-dependent reactive oxygen species.The indole side chain of Trp is vulnerable to^(1)O_(2),leading to the generation of oxidized Trp variants and priming EX1 for degradation by a membrane-bound FtsH protease.The perception of^(1)O_(2)via Trp643 oxidation and subsequent EX1 proteolysis facilitate chloroplast-to-nucleus retrograde signaling.In this study,we discovered that the EX1-like protein EX2 also undergoes^(1)O_(2)-dependent Trp530 oxidation and FtsH-dependent turnover,which attenuates^(1)O_(2)signaling by decelerating EX1-Trp643 oxidation and subsequent EX1 degradation.Consistent with this finding,the loss of EX2 function reinforces EX1-dependent retrograde signaling by accelerating EX1-Trp643 oxidation and subsequent EX1 proteolysis,whereas overexpression of EX2 produces molecular phenotypes opposite to those observed in the loss-of-function mutants of EX2.Intriguingly,phylogenetic analysis suggests that EX2 may have emerged evolutionarily to attenuate the sensitivity of EX1 toward^(1)O_(2).Collectively,these results suggest that EX2 functions as a negative regulator of the EX1 signalosome through its own^(1)O_(2)-dependent oxidation,providing a new mechanistic insight into the regulation of EX1-mediated^(1)O_(2)signaling.

关键词： EXECUTER1 EXECUTER2 singlet oxygen retrograde signaling Trp oxidation FtsH protease

Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

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Computers, Materials & Continua 2023年第11期77卷 2097-2121页

作者： Deepak Kumar Vinay Kukreja Ayush dogra Bhawna Goyal Talal Taha Ali Department of Computer Science&Engineering Chitkara University Institute of Engineering and TechnologyChitkara UniversityPunjab140401India Department of Electronics&Communication Engineering Chandigarh UniversityPunjab140413India Department of Dental Industry Techniques Al-Noor University CollegeNineveh41018Iraq

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

关键词： Wheat rust diseases agricultural region extraction models intercropping image processing feature extraction precision agriculture

Impact of geographical and seasonal temperature on sperm parameters in Indian men who were partners in subfertile couples-A retrospective analysis

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Asian pacific Journal of Reproduction 2022年第4期11卷 175-182页

作者： Yogita dogra Neeta Singh Neena Malhotra Reeta Mahey Vanamail Perumal Department of Obstetrics and Gynaecology Kamla Nehru State HospitalIndira Gandhi Medical CollegeShimla-Himachal PradeshIndia Department of Obstetrics and Gynaecology AIIMSNew DelhiIndia Statistics and Demography Department of Obstetrics and GynaecologyAIIMSNew DelhiIndia

Objective:To evaluate the impact of seasonal and geographical temperature on sperm parameters in Indian men who were partners in subfertile couples.Methods:A retrospective review of the records of semen analysis from January 2009 to December 2017 that was performed as part of primary evaluation of infertile couple was undertaken.Mean values of various semen parameters were compared between seasons using one-way analysis of variance test followed by Bonferroni pair wise post-hoc comparison test.Bivariate Pearson correlation coefficient was applied to measure the correlation between age,sperm parameters and annual temperature/seasons.The logistic regression analysis was further carried out to identify significant variables contributing to normal progressive motility of sperm.Results:A total of 3433 reports of semen samples were analysed.There was no significant seasonal variation in the mean volume,concentration,and total motility levels(P>0.05)except the mean values of progressive motility(P<0.001).The mean values of progressive motility during pre-monsoon were significantly higher compared to the corresponding values during monsoon and autumn seasons(P<0.01).In all the seasons,total motility had significant positive correlation with sperm concentration and progressive motility(P<0.05).Pre-monsoon emerged as the significant favourable season to get normal progressive motility level(OR 1.32,95%CI 1.04-1.68)compared to winter.The chances of getting normal progressive motility reduced due to longer abstinence period(OR 0.87,95%CI 0.80-0.93).When the temperature was more than 28℃,the likelihood of getting normal progressive motility decreased(OR 0.70,95%CI 0.51-0.95).Conclusions:The progressive motility of sperms significantly decreases from pre-monsoon to autumn with recovery towards winter,which substantiates the effect of rising temperature on the progressive motility of sperm.This is clinically important to counsel infertile patients,so that they can plan their treatment accordingly.

关键词： Infertility Seasonal variations Sperm Progressive motility Geographical temperature

Medical Image Fusion Based on Anisotropic Diffusion and Non-Subsampled Contourlet Transform

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Computers, Materials & Continua 2023年第7期76卷 311-327页

作者： Bhawna Goyal Ayush dogra Rahul Khoond Dawa Chyophel Lepcha Vishal Goyal Steven LFernandes Department of ECE Chandigarh UniversityMohali140413PunjabIndia Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Department of Electronics and Communication Engineering GLA UniversityMathuraIndia Department of Computer Science Design and JournalismCreighton UniversityNEUSA

The synthesis of visual information from multiple medical imaging inputs to a single fused image without any loss of detail and distortion is known as multimodal medical image fusion.It improves the quality of biomedical images by preserving detailed features to advance the clinical utility of medical imaging meant for the analysis and treatment of medical disor-ders.This study develops a novel approach to fuse multimodal medical images utilizing anisotropic diffusion(AD)and non-subsampled contourlet transform(NSCT).First,the method employs anisotropic diffusion for decomposing input images to their base and detail layers to coarsely split two features of input images such as structural and textural information.The detail and base layers are further combined utilizing a sum-based fusion rule which maximizes noise filtering contrast level by effectively preserving most of the structural and textural details.NSCT is utilized to further decompose these images into their low and high-frequency coefficients.These coefficients are then combined utilizing the principal component analysis/Karhunen-Loeve(PCA/KL)based fusion rule independently by substantiating eigenfeature reinforcement in the fusion results.An NSCT-based multiresolution analysis is performed on the combined salient feature information and the contrast-enhanced fusion coefficients.Finally,an inverse NSCT is applied to each coef-ficient to produce the final fusion result.Experimental results demonstrate an advantage of the proposed technique using a publicly accessible dataset and conducted comparative studies on three pairs of medical images from different modalities and health.Our approach offers better visual and robust performance with better objective measurements for research development since it excellently preserves significant salient features and precision without producing abnormal information in the case of qualitative and quantitative analysis.

关键词： Anisotropic diffusion biomedical medical health diseases adversarial attacks image fusion research and development precision

MRMR Based Feature Vector Design for Efficient Citrus Disease Detection

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Computers, Materials & Continua 2022年第9期72卷 4771-4787页

作者： Bobbinpreet Sultan Aljahdali Tripti Sharma Bhawna Goyal Ayush dogra Shubham Mahajan Amit Kant Pandit Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Ronin Institute Mont ClairNJ07043USA School of Electronics&Communication Engineering Shri Mata Vaishno Devi UniversityKatra182320India

In recent times,the images and videos have emerged as one of the most important information source depicting the real time scenarios.Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane.The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition.One of the application fields pertains to detection of diseases occurring in the plants,which are destroying the widespread fields.Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests.This is a tedious and time consuming process and does not suffice the accuracy levels.This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading.The digital images captured from the field’s forms the dataset which trains the machine learning models to predict the nature of the disease.The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images,appropriate segmentation methodology,feature vector development and the choice of machine learning algorithm.To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages.Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection.The training vector thus developed is capable of presenting the relationship between the feature values and the target class.In this article,a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is

关键词： Citrus diseases classification feature vector design plant disease detection redundancy reduction

Sensitivity Analysis of Contact Type Vibration Measuring Sensors

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Sound & Vibration 2022年第3期56卷 235-243页

作者： Mohit Dhanda Pankaj Pant Sourabh dogra Arpan Gupta Varun Dutt School of Engineering Indian Institute of TechnologyMandi175005India National Institute of Technology Hamirpur177001India School of Computing and Electrical Engineering Indian Institute of TechnologyMandi175005India

With the Internet of Things(IoT)era dawning in,we are surrounded by a plethora of sensors.The present paper focuses on MEMS-based vibration measuring accelerometers,which are ubiquitously present in smartphones,tablets,smartwatches/bands,etc.These contact type vibration sensors have the unique advantage of being very small,low cost,low power,less weighing,and easily accommodatable in electronics.However,the accuracy of these sensors needs to be quantified with respect to more accurate sensors.With this objective,the paper presents a comparison of the relative sensitivity of a MEMS-based accelerometer(MPU 6050),a Geophone,and a sensor from Xiaomi Y2 smartphone with respect to a more standard Piezoelectric ICP based accelerometer,when all sensors are tested on a shaker table.Data are measured with harmonic excitation over a frequency range of 2–184 Hz.The relative sensitivity of MPU 6050 was 90%accurate in the frequency range 18–116 Hz for RMS measurements.Other sensors such as the one used in the Xiaomi Y2 smartphone and the Geophone were less accurate.The relative sensitivity measured in this work can be used to obtain sensitivity and hence more accurate data from these low-cost accelerometers.

关键词： MEMS sensor frequency sensitivity

Preferred practice guidelines for retinopathy of prematurity screening during the COVID-19 pandemic

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World Journal of Clinical Pediatrics 2022年第3期11卷 215-220页

作者： Anand Vinekar Rajvardhan Azad Mangat Ram dogra Subhadra Jalali Pramod Bhende Parijat Chandra Narendran Venkatapathy Sucheta Kulkarni Pediatric Retina Narayana Nethralaya Eye InstituteBangalore 560010India Department of Ophthalmology Regional Institute of OphthalmologyIGIMSPatna 800014India Department of Ophthalmology Grewal Eye InstituteChandigarh 160009India Department of Retina LV Prasad Eye InstituteHyderabad 500034India Department of Retina Sankara NethralayaChennai 600006India Department of Ophthalmology All India Institute of Medical SciencesNew Delhi 110023India Department of Retina Aravind Eye HospitalCoimbatore 641014India Department of Ophthalmology H.V.Desai Eye HospitalPune 411028India

Retinopathy of prematurity(ROP)is the leading cause of preventable infant blindness in the world and predominantly affects babies who are born low birth weight and premature.India has the largest number of surviving preterm births born annually.ROP blindness can be largely prevented if there is a robust screening program which detects treatment requiring disease in time.ROP treatment must be provided within 48 h of reaching this threshold of treatment making it a relative emergency.During the severe acute respiratory syndromecoronavirus disease 2019 pandemic in 2020 ROP screening was disrupted throughout the world due to lockdowns and restriction of movement of these infants,their families,specialists and healthcare workers.The Indian ROP Society issued guidelines for ROP screening and treatment in March 2020,which was aimed at preserving the chain-of-care despite the potential limitations and hazards during the(ongoing)pandemic.This preferred practice guideline is summarized in this manuscript.

关键词： Retinopathy of prematurity Screening Preferred practice COVID-19 Pandemic Indian retinopathy of prematurity society

Clinical features and characteristics of retinopathy of prematurity in developing countries

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Annals of Eye Science 2018年第1期3卷 22-28页

作者： Mangat R.dogra Deeksha Katoch Department of Ophthalmology Advanced Eye CentrePostgraduate Institute of Medical Education and Research(PGIMER)ChandigarhIndia

Retinopathy of prematurity(ROP)is an emerging cause of childhood blindness in the developing countries.The low and middle-income countries are facing common challenges in the midst of the‘third epidemic’of ROP.Improvement in neonatal care facilities has increased survival of preterm babies.Lack of awareness and non-uniform standards of care in the ever-increasing number of neonatal intensive care units(NICUs)and special newborn care units(SNCUs)has resulted in this surge of ROP.Apart from low birth weight and the degree of prematurity,use of unblended supplemental oxygen,sepsis,anemia and blood transfusion are important risk factors associated with ROP in developing countries.Atypical forms of aggressive posterior ROP(APROP)are seen in heavier birth weight babies in the developing countries.Prevention of ROP by good quality neonatal care,timely diagnosis by mandatory ROP screening in NICUs and training manpower for laser treatment of ROP requires close collaboration between the neonatologists,ophthalmologists and the policy makers.Team approach and inter-disciplinary co-ordination are keys in a nation’s drive to fight this preventable cause of blindness.

关键词： Childhood blindness retinopathy of prematurity(ROP) screening neonatologist