International Journal of Current Research and Review
ISSN: 2231-2196 (Print)ISSN: 0975-5241 (Online)
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IJCRR - 13(12), June, 2021

Pages: 210-214

Date of Publication: 22-Jun-2021


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3D Densealexnet Model for Brain Tumour Segmentation

Author: M. Sumithra, S. Malathi

Category: Healthcare

Abstract:Background: The collection of anomalous cells within or around the brain is stated as a brain tumour. Automatic brain tumour segmentation is considered a challenging task due to complexity and gradient diffusion. To improve the segmentation of 3D brain MRI images Deep Neural Network (DNN) is evolved. However, it is subjected to the drawback of training computational power and complexity. Objective: In this paper, proposed a 3D Dense AlexNet model with backpropagation for segmentation of tumour in brain MRI images. The developed architecture consists of Neural Network for processing input 3D images. This paper focused on improving the overall segmentation process with the Alexnet model for 3D brain images for performance improvement. Method: Based on the training and validation test self-constrained 3D Dense ALexNet model is developed. Within the 3D Dense AlexNet backpropagation is adopted for removing complexity in the testing process and accuracy improvement. Based on the training and testing process 3D MRI image sequences are trained and processed for segmentation on the tumour. Result: The analysis of results expressed that the proposed 3D Dense AlexNet exhibits improved segmentation performance. Based on the proposed 3D AlexNet architecture MRI images are segmented with minimal time. The performance of the proposed 3D Dense AlexNet model exhibited the improved accuracy of tumour detection with reduced computational complexity

Keywords: 3D Brain MRI, Dense AlexNet, Back Propagation, Segmentation, Deep Neural Network (DNN), Neural Network

Full Text:

                 INTRODUCTION

A tumour is a collection or mass of abnormal cells that occur in various parts of the body. A tumour can result in cancer, which is the main reason for death and accounts for around 13% of every death worldwide. The cancer occurrence rate is rising at an alarming rate in the world. Therefore, tumour detection is significant in previous stages.1 The mast of abnormal cells that grow in or around the brain is called a brain tumour.

It poses a risk to the healthy brain by either destroying or invading normal brain tissue. The tumour in the brain is emerged due to the existence of a glial cell known as GLIOMAS. Those cells are classified and graded from values 1 to 4. In this assigned grade, tumour belongs to grades 3 and 4 are stated as malignant or cancerous cell. The tumour belongs to grade 1 and 2 is stated as benign or non-cancerous cells.2 To identify brain tumour Magnetic Resonance Imaging (MRI) is utilized for the detection of modality to assess tumours in the brain. MRI assists the physician in the investigation of soft tissues in the human brain. MRI offers soft tissues with four different types such as T1-weighted (T1w), T1-weighted with contrast enhancement (T1wc), T2-weighted (T2w), and Fluid Attenuated Inversion Recovery (FLAIR).3 In this, healthy tissue is stated as T1-weighted (T1w).

Corresponding Author: M.Sumithra, Research scholar, Department of computer science and engineering, Sathyabama institute of science and technology, Chennai, India.

Both T2w and T1w are used for the detection of tumours which provides a bright tumour border. The FLAIR is involved in the isolation of the oedema region in the brain from CSF (cerebrospinal fluid). However, the identification of boundaries of the tumour is difficult due to homogeneity with different sequence intensities.4

Identification of brain tumour from MRI consist of different stages. Segmentation is termed to be a significant but tough step for the classification of medical imaging and its analysis.5 To segment MRI segmentation Convolutional Neural Networks (CNNs) are utilized with multi-modal factors. The CNN model consists of several functions such as extraction and classification of feature with a single model. However, existing CNN is subjected to complexity issues and limited accuracy.6 In recent years, Deep Convolutional Neural Network (DCNN) strategy is adopted for the extraction and classification of features. In, proposed a DCNN model was integrated with convolutional kernels for tumour segmentation in MRI images. In DCNN, a small kernel filter is adopted for cascade connection of convolutional layers with small kernel filters. 7  In developed an architecture with a parallel cascade connection of CNN. The cascaded network incorporates training with balanced classes and the second stage involved in the refinement of the last layer with several samples at each class.8

In developed an algorithm based on utilization of fuzzy c-means clustering through the utilization of membership function.9 Based on estimated membership function centres are clustered and simultaneously generated. Recently, in 10 presented a modified FCM algorithm for segmentation of MRI image. We developed a fuzzy segmentation for MRI images. The MRI image segmentation is based on the estimation of IIH with the characterization of Gaussian function. 9 A research conducted developed a multi-objective framework for 3D MRI image segmentation. The proposed approach incorporates a two-stage fuzzy multi-objective framework (2sFMoF). Also, in 13 constructed an FCM algorithm spatial information algorithm for segmentation noisy MRI images. Also, it contains local membership as an objective function for MRI image segmentation. 10,11 In developed a conditional spatial FCM(csFCM) for segmentation of MRI brain image. Similarly, in15 constructed a deep convolutional neural network for MRI image segmentation with the exploitation of convolutional kernels. However, this technique fails to provides an accurate classification of brain tumours. To overcome those limitations this research presented a DenseAlexNet model with a backpropagation classifier. evaluation metrics. 12,13

This paper developed a Dense AlexNet for tumour segmentation for brain tumour diagnosis. Also, the backpropagation scheme is applied for the classification of tumour regions in MRI images of the brain. 14

3D Dense Alex Net for MRI Segmentation

To achieve segmentation accuracy of 3D brain MRI images this paper uses 3D DenseAlexNet mode. The data for Multimodal Brain Tumour Segmentation is based on MICCAI 2012 conference. The developed Dense AlexNet model performance is based on the estimation of directions in a 3D image. The Dense AlexNet is involved in the extraction of features from brain images with the discriminative representation of MRI images through pooling layers. The next layer of Dense AlexNet generates high-level MRI image features for categorizing features in MRI images. In the next stage, the processed samples are masked for the identification of high-level features of MRI 3D images. With the object localization process in 3D Dense AlexNet, middle features are processed within the network. Through the incorporation of the backpropagation tumour region of the MRI image is segmented. To process input data MRI brain image is considered for pre-processing and segmentation of the tumour part. The feature of MRI brain images is extracted based on GLCM features with selected Region of Interest (ROI) for segmentation of the tumour part. The developed Dense AlexNet based on the adjusted pixel values tumour is segmented concerning position and area. Finally, classification is performed with Backpropagation for obtaining a resultant image with dataset images to identify it is benign or malignant. Initially, the proposed Dense AlexNet perform image pre-processing for removal of noise. To enhance the quality of the image certain features are examined to display image processing. The process involved in MRI pre-processing of MRI brain images is filtering of noise, pseudo-colouring, sharpening, and magnifying. The steps involved in improving image quality are image display, image analysis, and feature extraction. This paper uses median filtering for processing for the elimination of noises in the image. The applied median filter performs a linear operation for the elimination of salt and pepper noise. The process of median filtering is involved in the reduction of noise to preserve image edges. The proposed Dense AlexNet examines the image feature pixel, weight, depth, and colour before classification steps. Image segmentation is involved in the identification of object boundaries and location. Image explicit segmentation in involved in each pixel allocation based on assigned labels with similar label characteristics. Image segmentation outcome covers a complete image or performs image extraction. Every image pixels are based on characteristics of image property, texture, colour, and intensity. The Dense AlexNet performs classification of the image with backpropagation for MRI image training and testing. The proposed Dense AlexNet perform image classification using weighted estimation. The segmented images are trained and tested for image classification. The performance of the proposed Dense AlexNet is compared with image datasets. With image dataset classification tumour region of MRI images are segmented and classified as either normal or abnormal tumour images.

RESULTS

The performance of the proposed Dense AlexNet uses a Backpropagation classifier for segmentation and classification of tumour in MRI images. The proposed Dense AlexNet is implemented using MATLAB 2019 for analysis. To segment tumour in MRI image, Dense AlexNet is designed and obtained results are presented as follows. In figure 1 and 2, the input image considered for segmentation of the MRI brain image and figure 2 provides the pre-processed image for the input 3D MRI image.

In figure 3, the bounding box for the pre-processed image is presented. The Dense AlexNet involved in the processing and quality enhancement of input 3D MRI images. To highlight the tumour within the input image bounding box is adopted. The bounding box estimates the image features and highlights the tumour region. In figure 4 segmented tumour region is presented for input 3D MRI brain image. In figure 5 detected tumour region of the proposed dense AlexNet is presented.

DISCUSSION

               The developed 3D AlexNet model involved in the segmentation of 3D MRI brain images for segmentation. The developed 3D AlexNet model utilizes a backpropagation approach for segmentation of 3D MRI. Based on identified region proposed Dense AlexNet estimate the location of the tumour in the input MRI image and segment tumour part. The proposed Dense AlexNet significantly estimate the 3D view of the input image based on consideration of the input 3D MRI image of the brain for segmentation of tumour in input 3D MRI image. The comparative analysis of results expressed that the proposed 3D AlexNet model exhibits higher accuracy rather than other existing technique. In table 1, time and accuracy of proposed 3D AlexNet with existing Convolutional Neural Network (CNN) and Deep Convolutional Neural Network (DCNN). Table 1 shows the overall comparison.

In figure 8 comparative plot for segmentation time and accuracy is presented

               The simulation analysis expressed that the proposed 3D AlexNet model exhibits a higher accuracy value than the existing CNN and DCNN. Also, the proposed 3D AlexNet significantly reduces segmentation time compared with CNN and DCNN.

CONCLUSION

A brain tumour is caused due to the anomalous growth of tissues within the human brain, this leads to increase mortality. The proper diagnosis is required for reducing mortality rate, hence image processing techniques are evolved for effective diagnosis of brain tumours. Usually, the processing of MRI brain images is a complex task due to the complexity of the human brain structure. To improve the diagnosis process in MRI brain images, this paper proposed a Dense AlexNet for the segmentation of tumours. The proposed Dense AlexNet uses a Backpropagation classifier for tumour detection in the region. The comparative analysis of proposed 3D AlexNet architecture with conventional CNN and DCNN exhibited that improved accuracy with reduced segmentation time. The accuracy of the proposed 3D AlexNet is ~3% improved. Similarly, segmentation time is reduced on average by ~30 sec.  In the future, the proposed segmentation scheme is processed with a sophisticated algorithm for detection, segmentation, and classification of brain tumour for medical applications.

ACKNOWLEDGMENT

The authors acknowledge the immense help received from the scholars whose articles are cited and included in references to this manuscript. The authors are also grateful to authors/editors/publishers of all those articles, journals, and books from which the literature for this article has been reviewed and discussed.

Conflict of Interest: Nil

 Source of Funding: Nil

References:

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  8. Kamnitsas K, Ledig C, Newcombe V. F, Simpson J. P, Kane A. D, Menon D. K and Glocker B Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Med Ima Analy.  2017;.36: 61-78.

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Announcements

Dr. Pramod Kumar Manjhi joined Editor-in-Chief since July 2021 onwards

COPE guidelines for Reviewers

SCOPUS indexing: 2014, 2019 to 2021


Awards, Research and Publication incentive Schemes by IJCRR

Best Article Award: 

One article from every issue is selected for the ‘Best Article Award’. Authors of selected ‘Best Article’ are rewarded with a certificate. IJCRR Editorial Board members select one ‘Best Article’ from the published issue based on originality, novelty, social usefulness of the work. The corresponding author of selected ‘Best Article Award’ is communicated and information of award is displayed on IJCRR’s website. Drop a mail to editor@ijcrr.com for more details.

Women Researcher Award:

This award is instituted to encourage women researchers to publish her work in IJCRR. Women researcher, who intends to publish her research work in IJCRR as the first author is eligible to apply for this award. Editorial Board members decide on the selection of women researchers based on the originality, novelty, and social contribution of the research work. The corresponding author of the selected manuscript is communicated and information is displayed on IJCRR’s website. Under this award selected women, the author is eligible for publication incentives. Drop a mail to editor@ijcrr.com for more details.

Emerging Researcher Award:

‘Emerging Researcher Award’ is instituted to encourage student researchers to publish their work in IJCRR. Student researchers, who intend to publish their research or review work in IJCRR as the first author are eligible to apply for this award. Editorial Board members decide on the selection of student researchers for the said award based on originality, novelty, and social applicability of the research work. Under this award selected student researcher is eligible for publication incentives. Drop a mail to editor@ijcrr.com for more details.


Best Article Award

A study by Dorothy Ebere Adimora et al. entitled \"Remediation for Effects of Domestic Violence on Psychological well-being, Depression and Suicide among Women During COVID-19 Pandemic: A Cross-cultural Study of Nigeria and Spain\" is awarded Best Article of Vol 14 issue 23
A study by Muhas C. et al. entitled \"Study on Knowledge & Awareness About Pharmacovigilance Among Pharmacists in South India\" is awarded Best article for Vol 14 issue 22
A study by Saurabh Suvidha entitled \"A Case of Mucoid Degeneration of Uterine Fibroid with Hydrosalphinx and Ovarian Cyst\" is awarded Best article of Vol 14 issue 21
A study by Alice Alice entitled \"Strengthening of Human Milk Banking across South Asian Countries: A Next Step Forward\" is awarded Best article of Vol 14 issue 20
A study by Sathyanarayanan AR et al. entitled \"The on-task Attention of Individuals with Autism Spectrum Disorder-An Eye Tracker Study Using Auticare\" is awarded Best article of Vol 14 issue 19
A study by Gupta P. et al. entitled \"A Short Review on \"A Novel Approach in Fast Dissolving Film & their Evaluation Studies\" is awarded Best Article of Vol 14 issue 18.
A study by Shafaque M. et al. entitled \"A Case-Control Study Performed in Karachi on Inflammatory Markers by Ciprofloxacin and CoAmoxicillin in Patients with Chronic Suppurative Otitis Media\" is awarded Best Article of Vol 14 issue 17
A study by Ali Nawaz et al. entitled \"A Comparative Study of Tubeless versus Standard Percutaneous Nephrolithotomy (PCNL) \? A Randomized Controlled Study\" is awarded Best Article for Vol 14 issue 16.
A study by Singh R. et al. entitled \"A Prospective Study to Find the Association of Astigmatism in Patients of Vernal Keratoconjunctivitis (VKC) in a Tertiary Health Care Centre in India (Vindhya Region MP)\" is awarded Best Article for Vol 14 issue 15
A Study by Humaira Tahir et al. entitled "Comparison of First Analgesic Demand after Major Surgeries of Obstetrics and Gynecology between Pre-Emptive Versus Intra-Operative Groups by Using Intravenous Paracetamol: A Cross-Sectional Study" is awarded Best Article for Vol 14 issue 14
A Study by Monica K. entitled "Risk Predictors for Lymphoma Development in Sjogren Syndrome - A Systematic Review" is awarded Best Article for Vol 14 issue 13
A Study by Mokhtar M Sh et al. entitled "Prevalence of Hospital Mortality of Critically Ill Elderly Patients" is awarded Best Article for Vol 14 issue 12
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A Study by Pandya S. et al. entitled "Acute and 28-Day Repeated Dose Subacute Toxicological Evaluation of Coroprotect Tablet in Rodents" is awarded Best Article for Vol 14 issue 10
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A Study by Vinita S & Ayushi S entitled "Role of Colour Doppler and Transvaginal Sonography for diagnosis of endometrial pathology in women presenting with Abnormal Uterine Bleeding" is awarded Best Article for Vol 14 issue 08
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A Study by Divya MP et al. entitled "Non-Echoplanar Diffusion-Weighted Imaging and 3D Fiesta Magnetic Resonance Imaging Sequences with High Resolution Computed Tomography Temporal Bone in Assessment and Predicting the Outcome of Chronic Suppurative Otitis Media with Cholesteatoma" is awarded Best Article for Vol 14 issue 06
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A Study by Ajai KG & Athira KN entitled "Patients’ Gratification Towards Service Delivery Among Government Hospitals with Particular Orientation Towards Primary Health Centres" is awarded Best Article for Vol 14 issue 04
A Study by Mbungu Mulaila AP et al. entitled "Ovarian Pregnancy in Kindu City, D.R. Congo - A Case Report" is awarded Best Article for Vol 14 issue 03
A Study by Maryam MJ et al. entitled "Evaluation Serum Chemerin and Visfatin Levels with Rheumatoid Arthritis: Possible Diagnostic Biomarkers" is awarded Best Article for Vol 14 issue 02
A Study by Shanthan KR et al. entitled "Comparison of Ultrasound Guided Versus Nerve Stimulator Guided Technique of Supraclavicular Brachial Plexus Block in Patients Undergoing Upper Limb Surgeries" is awarded Best Article for Vol 14 issue 01
A Study by Amol Sanap et al. entitled "The Outcome of Coxofemoral Bypass Using Cemented Bipolar Hemiarthroplasty in the Treatment of Unstable Intertrochanteric Fracture of Femur in a Rural Setup" is awarded Best Article Award of Vol 13 issue 24
A Study by Manoj KP et al. entitled "A Randomized Comparative Clinical Trial to Know the Efficacy of Ultrasound-Guided Transversus Abdominis Plane Block Against Multimodal Analgesia for Postoperative Analgesia Following Caesarean Section" is awarded Best Article Award of Vol 13 issue 23
A Study by Karimova II et al. entitled "Changes in the Activity of Intestinal Carbohydrases in Alloxan-Induced Diabetic Rats and Their Correction with Prenalon" is awarded Best Article of Vol 13 issue 22
A Study by Ashish B Roge et al. entitled "Development, Validation of RP-HPLC Method and GC MS Analysis of Desloratadine HCL and It’s Degradation Products" is awarded Best Article of Vol 13 issue 21
A Study by Isha Gaurav et al. entitled "Association of ABO Blood Group with Oral Cancer and Precancer – A Case-control Study" is awarded Best Article for Vol 13 issue 20
A Study by Amr Y. Zakaria et al. entitled "Single Nucleotide Polymorphisms of ATP-Binding Cassette Gene(ABCC3 rs4793665) affect High Dose Methotrexate-Induced Nephrotoxicity in Children with Osteosarcoma" is awarded Best Article for Vol 13 issue 19
A Study by Kholis Ernawati et al. entitled "The Utilization of Mobile-Based Information Technology in the Management of Dengue Fever in the Community Year 2019-2020: Systematic Review" is awarded Best Article for Vol 13 issue 18
A Study by Bhat Asifa et al. entitled "Efficacy of Modified Carbapenem Inactivation Method for Carbapenemase Detection and Comparative Evaluation with Polymerase Chain Reaction for the Identification of Carbapenemase Producing Klebsiella pneumonia Isolates" is awarded Best Article for Vol 13 issue 17
A Study by Gupta R. et al. entitled "A Clinical Study of Paediatric Tracheostomy: Our Experience in a Tertiary Care Hospital in North India" is awarded Best Article for Vol 13 issue 16
A Study by Chandran Anand et al. entitled "A Prospective Study on Assessment of Quality of Life of Patients Receiving Sorafenib for Hepatocellular Carcinoma" is awarded Best article for Vol 13 issue 15
A Study by Rosa PS et al. entitled "Emotional State Due to the Covid – 19 Pandemic in People Residing in a Vulnerable Area in North Lima" is awarded Best Article for Vol 13 issue 14
A Study by Suvarna Sunder J et al. entitled "Endodontic Revascularization of Necrotic Permanent Anterior Tooth with Platelet Rich Fibrin, Platelet Rich Plasma, and Blood Clot - A Comparative Study" is awarded Best Article for Vol 13 issue 13
A Study by Mona Isam Eldin Osman et al. entitled "Psychological Impact and Risk Factors of Sexual Abuse on Sudanese Children in Khartoum State" is awarded Best Article for Vol 13 issue 12
A Study by Khaw Ming Sheng & Sathiapriya Ramiah entitled "Web Based Suicide Prevention Application for Patients Suffering from Depression" is awarded Best Article for Vol 13 issue 11
A Study by Purushottam S. G. et al. entitled "Development of Fenofibrate Solid Dispersions for the Plausible Aqueous Solubility Augmentation of this BCS Class-II Drug" is awarded Best article for Vol 13 issue 10
A Study by Kumar S. et al. entitled "A Study on Clinical Spectrum, Laboratory Profile, Complications and Outcome of Pediatric Scrub Typhus Patients Admitted to an Intensive Care Unit from a Tertiary Care Hospital from Eastern India" is awarded Best Article for Vol 13 issue 09
A Study by Mardhiah Kamaruddin et al. entitled "The Pattern of Creatinine Clearance in Gestational and Chronic Hypertension Women from the Third Trimester to 12 Weeks Postpartum" is awarded Best Article for Vol 13 issue 08
A Study by Sarmila G. B. et al. entitled "Study to Compare the Efficacy of Orally Administered Melatonin and Clonidine for Attenuation of Hemodynamic Response During Laryngoscopy and Endotracheal Intubation in Gastrointestinal Surgeries" is awarded Best Article for Vol 13 issue 07
A Study by M. Muthu Uma Maheswari et al. entitled "A Study on C-reactive Protein and Liver Function Tests in Laboratory RT-PCR Positive Covid-19 Patients in a Tertiary Care Centre – A Retrospective Study" is awarded Best Article of Vol 13 issue 06 Special issue Modern approaches for diagnosis of COVID-19 and current status of awareness
A Study by Gainneos PD et al. entitled "A Comparative Evaluation of the Levels of Salivary IgA in HIV Affected Children and the Children of the General Population within the Age Group of 9 – 12 Years – A Cross-Sectional Study" is awarded Best Article of Vol 13 issue 05 Special issue on Recent Advances in Dentistry for better Oral Health
A Study by Alkhansa Mahmoud et al. entitled "mRNA Expression of Somatostatin Receptors (1-5) in MCF7 and MDA-MB231 Breast Cancer Cells" is awarded Best Article of Vol 13 issue 06
A Study by Chen YY and Ghazali SRB entitled "Lifetime Trauma, posttraumatic stress disorder Symptoms and Early Adolescence Risk Factors for Poor Physical Health Outcome Among Malaysian Adolescents" is awarded Best Article of Vol 13 issue 04 Special issue on Current Updates in Plant Biology to Medicine to Healthcare Awareness in Malaysia
A Study by Kumari PM et al. entitled "Study to Evaluate the Adverse Drug Reactions in a Tertiary Care Teaching Hospital in Tamilnadu - A Cross-Sectional Study" is awarded Best Article for Vol 13 issue 05
A Study by Anu et al. entitled "Effectiveness of Cytological Scoring Systems for Evaluation of Breast Lesion Cytology with its Histopathological Correlation" is awarded Best Article of Vol 13 issue 04
A Study by Sharipov R. Kh. et al. entitled "Interaction of Correction of Lipid Peroxidation Disorders with Oxibral" is awarded Best Article of Vol 13 issue 03
A Study by Tarek Elwakil et al. entitled "Led Light Photobiomodulation Effect on Wound Healing Combined with Phenytoin in Mice Model" is awarded Best Article of Vol 13 issue 02
A Study by Mohita Ray et al. entitled "Accuracy of Intra-Operative Frozen Section Consultation of Gastrointestinal Biopsy Samples in Correlation with the Final Histopathological Diagnosis" is awarded Best Article for Vol 13 issue 01
A Study by Badritdinova MN et al. entitled "Peculiarities of a Pain in Patients with Ischemic Heart Disease in the Presence of Individual Combines of the Metabolic Syndrome" is awarded Best Article for Vol 12 issue 24
A Study by Sindhu Priya E S et al. entitled "Neuroprotective activity of Pyrazolone Derivatives Against Paraquat-induced Oxidative Stress and Locomotor Impairment in Drosophila melanogaster" is awarded Best Article for Vol 12 issue 23
A Study by Habiba Suhail et al. entitled "Effect of Majoon Murmakki in Dysmenorrhoea (Usre Tams): A Standard Controlled Clinical Study" is awarded Best Article for Vol 12 issue 22
A Study by Ghaffar UB et al. entitled "Correlation between Height and Foot Length in Saudi Population in Majmaah, Saudi Arabia" is awarded Best Article for Vol 12 issue 21
A Study by Siti Sarah Binti Maidin entitled "Sleep Well: Mobile Application to Address Sleeping Problems" is awarded Best Article for Vol 12 issue 20
A Study by Avijit Singh"Comparison of Post Operative Clinical Outcomes Between “Made in India” TTK Chitra Mechanical Heart Valve Versus St Jude Mechanical Heart Valve in Valve Replacement Surgery" is awarded Best Article for Vol 12 issue 19
A Study by Sonali Banerjee and Mary Mathews N. entitled "Exploring Quality of Life and Perceived Experiences Among Couples Undergoing Fertility Treatment in Western India: A Mixed Methodology" is awarded Best Article for Vol 12 issue 18
A Study by Jabbar Desai et al. entitled "Prevalence of Obstructive Airway Disease in Patients with Ischemic Heart Disease and Hypertension" is awarded Best Article for Vol 12 issue 17
A Study by Juna Byun et al. entitled "Study on Difference in Coronavirus-19 Related Anxiety between Face-to-face and Non-face-to-face Classes among University Students in South Korea" is awarded Best Article for Vol 12 issue 16
A Study by Sudha Ramachandra & Vinay Chavan entitled "Enhanced-Hybrid-Age Layered Population Structure (E-Hybrid-ALPS): A Genetic Algorithm with Adaptive Crossover for Molecular Docking Studies of Drug Discovery Process" is awarded Best article for Vol 12 issue 15
A Study by Varsha M. Shindhe et al. entitled "A Study on Effect of Smokeless Tobacco on Pulmonary Function Tests in Class IV Workers of USM-KLE (Universiti Sains Malaysia-Karnataka Lingayat Education Society) International Medical Programme, Belagavi" is awarded Best article of Vol 12 issue 14, July 2020
A study by Amruta Choudhary et al. entitled "Family Planning Knowledge, Attitude and Practice Among Women of Reproductive Age from Rural Area of Central India" is awarded Best Article for special issue "Modern Therapeutics Applications"
A study by Raunak Das entitled "Study of Cardiovascular Dysfunctions in Interstitial Lung Diseas epatients by Correlating the Levels of Serum NT PRO BNP and Microalbuminuria (Biomarkers of Cardiovascular Dysfunction) with Echocardiographic, Bronchoscopic and HighResolution Computed Tomography Findings of These ILD Patients" is awarded Best Article of Vol 12 issue 13 
A Study by Kannamani Ramasamy et al. entitled "COVID-19 Situation at Chennai City – Forecasting for the Better Pandemic Management" is awarded best article for  Vol 12 issue 12
A Study by Muhammet Lutfi SELCUK and Fatma entitled "Distinction of Gray and White Matter for Some Histological Staining Methods in New Zealand Rabbit's Brain" is awarded best article for  Vol 12 issue 11
A Study by Anamul Haq et al. entitled "Etiology of Abnormal Uterine Bleeding in Adolescents – Emphasis Upon Polycystic Ovarian Syndrome" is awarded best article for  Vol 12 issue 10
A Study by entitled "Estimation of Reference Interval of Serum Progesterone During Three Trimesters of Normal Pregnancy in a Tertiary Care Hospital of Kolkata" is awarded best article for  Vol 12 issue 09
A Study by Ilona Gracie De Souza & Pavan Kumar G. entitled "Effect of Releasing Myofascial Chain in Patients with Patellofemoral Pain Syndrome - A Randomized Clinical Trial" is awarded best article for  Vol 12 issue 08
A Study by Virendra Atam et. al. entitled "Clinical Profile and Short - Term Mortality Predictors in Acute Stroke with Emphasis on Stress Hyperglycemia and THRIVE Score : An Observational Study" is awarded best article for  Vol 12 issue 07
A Study by K. Krupashree et. al. entitled "Protective Effects of Picrorhizakurroa Against Fumonisin B1 Induced Hepatotoxicity in Mice" is awarded best article for issue Vol 10 issue 20
A study by Mithun K.P. et al "Larvicidal Activity of Crude Solanum Nigrum Leaf and Berries Extract Against Dengue Vector-Aedesaegypti" is awarded Best Article for Vol 10 issue 14 of IJCRR
A study by Asha Menon "Women in Child Care and Early Education: Truly Nontraditional Work" is awarded Best Article for Vol 10 issue 13
A study by Deep J. M. "Prevalence of Molar-Incisor Hypomineralization in 7-13 Years Old Children of Biratnagar, Nepal: A Cross Sectional Study" is awarded Best Article for Vol 10 issue 11 of IJCRR
A review by Chitra et al to analyse relation between Obesity and Type 2 diabetes is awarded 'Best Article' for Vol 10 issue 10 by IJCRR. 
A study by Karanpreet et al "Pregnancy Induced Hypertension: A Study on Its Multisystem Involvement" is given Best Paper Award for Vol 10 issue 09

List of Awardees

A Study by Ese Anibor et al. "Evaluation of Temporomandibular Joint Disorders Among Delta State University Students in Abraka, Nigeria" from Vol 13 issue 16 received Emerging Researcher Award


A Study by Alkhansa Mahmoud et al. entitled "mRNA Expression of Somatostatin Receptors (1-5) in MCF7 and MDA-MB231 Breast Cancer Cells" from Vol 13 issue 06 received Emerging Researcher Award


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Disclaimer: International Journal of Current Research and Review (IJCRR) provides platform for researchers to publish and discuss their original research and review work. IJCRR can not be held responsible for views, opinions and written statements of researchers published in this journal.



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International Journal of Current Research and Review (IJCRR) provides platform for researchers to publish and discuss their original research and review work. IJCRR can not be held responsible for views, opinions and written statements of researchers published in this journal

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