Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Cancer is one of the dreadful diseases in today’s world. Skin cancer is one among those. Manual methods have been available, still a contribution towards computer aided diagnostic in the field of medicine plays a challenging role. The objective of the paper is to detect and classify the skin image and find if it is a melanoma or non melanoma images. This paper includes the method for image enhancement as adaptive median filter, segmentation as a hybrid method and the feature extraction to be a hybrid method and finally the KNN classifier is used to classify the images. The total of 600 images is taken and the efficiency is said to be 96.8%. © IJSTR 2020.

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

Department of Analytics

International Journal of Scientific and Technology Research

Detection and classification of human malignant melanoma using cad approach

Failure of implants is a serious concern in the orthopedic field, due to loosening of the parts or biofilm formation. This leads to secondary surgery increasing the cost for the patients. The analysis of the ability of the implants to be resistant to infection or susceptible to biofilm growth before implantation could minimize this issue. The aim of this study is to investigate the ability to form biofilm on composite scaffolds, made up of polymer and calcium phosphates. The growth and proliferation of the microorganisms was evaluated quantitatively for biofilm formation by MTT assay and viable cell count (VCC) by vortexing. The surface colony morphology of biofilm on scaffold was observed using scanning electron microscopy. Biofilm formation was significantly higher on BG5 (p<0.05) as measured by MTT assay. But no profound difference was observed by viable cell count. Colony morphology analysis also showed a dense layer of biofilm on BG5, whereas only microcolonies were formed on other samples. BG5 is relatively more susceptible to biofilm formation compared to other compositions. This study also highlights the use of MTT assay for effective quantification of biofilm in scaffolds. © 2019 Elsevier Ltd. All rights reserved.

Department of Database Systems

Department of Micro and Nanoelectronics

School of Electronics Engineering

Department of Manufacturing Engineering

School of Mechanical Engineering

Department of Bio-Sciences

School of Bio Sciences and Technology

Materials Today: Proceedings

Biofilm formation by S.aureus on composite scaffolds – A qualitative and quantitative in vitro analysis

The aim of this study was to conduct a systematic review and meta-analysis and determine the prevalence of diabetic nephropathy (DN) among Arab patients with T1D. A systematic literature search was conducted using 4 different literature databases (PubMed, ScienceDirect, Web of Science, and Embase) to capture all relevant data about Arab patients with T1D that had DN. Meta-analysis and systematic review were performed using the random effect model, and the heterogeneity of the studies was assessed using the Q-test, I2, and Tau-squared statistics. Publication bias was assessed using the funnel-plot test. Our search strategy captured 372 studies in only 10 out of the 22 Arab countries in a period of 48 years (1969-2017); of which, 41 met our inclusion criteria for full article analysis, of those, 15 were eligible for meta-analysis. We estimated the prevalence of DN among Arab people with T1D to be 18.2% (95% confidence interval 13.1%-24.8%). In conclusion, DN prevalence is underexplored among Arab patients with T1D and represents a significant risk for the well-being of Arab patients with T1D. Therefore, there is an urgent need for comprehensive epidemiological studies for DN among Arab patients with T1D.

World University root node

Department of Integrative Biology

Diabetes/Metabolism Research and Reviews

Prevalence of nephropathy in type 1 diabetes in the Arab world: A systematic review and meta-analysis

VIT Unitversity

Lecture Notes in Electrical Engineering Frontier Computing

Study of CR Based U-LTE Co-existence Under Varying Wi-Fi Standards

Cancer is a deadly disease in today's world. Various types of cancers are spreading for which skin cancer becomes a very common cancer nowadays. Skin cancer can be of two types namely melanoma and non melanoma cancer. The objective of this paper is to detect and classify the benign and the normal image. Benign meaning the normal image, melanoma the cancerous one. And more over compare the various classification algorithms. Detection of skin cancer in earlier stages can be a life saving process. The detection of skin cancer includes four important stages namely Pre-processing, Segmentation, Feature Extraction and Classification. Detection can help in curing the cancer and hence detection plays a very vital role. In this paper, pre-processing the first and the foremost part of image processing which helps in noise removal is done by means of the median filter where the output of the median filter which is fed as an input to the histogram equalization phase of the pre-processing stage, then the input of the histogram equalized image is fed as an input to the segmentation phase where Otsu's thresholding is done to separate the foreground and the background. The segmentation helps to identify the region of interest, Now using the area, mean, variance and standard deviation of the extracted output from the segmentation phase the calculations for feature extraction is carried and the output is fed into classifiers like Support Vector Machine (SVM), K- Nearest Neighbor (KNN), Decision tree(DT) and Boosted Tree(BT).Comparison of the classification is done. The algorithm shows the accuracy of the classification rate of KNN is 92.70%, SVM is 93.70%, Decision tree (DT) is 89.5% and finally the boosted tree (BT) is 84.30%.

International Journal of Intelligent Engineering and Systems

Automatic Detection and Classification of Skin Cancer

Advancement in Computer Aided Diagnostic system (CAD) enhances the detection and classification of domain experts and reduces the time rapidly for them. The CAD systems can be used in hospitals as an alternate method. The objective of the paper is to present the effectiveness of the detection and classification of skin cancer. The proposed methodology concentrates on comparing the median filter and Adaptive Median Filter (AMF) and suggesting on one, the segmentation can be done by a hybrid approach where the marker controlled watershed algorithm is fused with the active contour algorithm, the feature extraction is done with the help of basic statistical methods and the Grey Level Co-Occurrence Matrix (GLCM) with the Support Vector Machine (SVM) for classification. SVM is used to classify the input as cancerous or not. The experiment is carried out on 250 images consists of 100 normal images and 150 abnormal images (benign and melanoma images) from a skin dataset. The classification accuracy shows 94% after the classification. © 2017, Scientific Publishers of India. All rights reserved.

Biomedical Research (India)

A hybrid segmentation approach for detection and classification of skin cancer

Cancer is one of the deadly diseases in today’s world. There are various types of cancer brain, lung, skin, liver etc. Cancer detection has been a challenging task. Early detection of cancer has bright chance of curing the disease. Detection takes a very crucial role in curing the deadly disease. The process of detection can take preprocessing, segmentation, feature extraction and classification. Preprocessing is the stage where the noise could be removed segmentation can help in splitting the image into various fields and feature extraction could help in extracting the feature and classification can classify and detect the final cells. This paper discusses on different papers which reviews on the detection of skin cancer. © RJPT All right reserved.

Research Journal of Pharmacy and Technology

Detection of Skin Cancer Cells-A Review

Due to increasing amount of data, the documents these days are digitized and kept in a digital form. This is either done by scanning of an image or capturing an image using digital Camera. During this process the image may sometimes be skewed from its original position. This requires the need to deskew the images in order to store them in proper manner. This paper deals with the problem of skewing of images by introducing an algorithm that helps in deskewing the document images. The algorithm efficiently works for binary document images. The algorithm takes an input image, calculates the skew angle and then performs several mathematical operations in order to perform skew correction. The proposed algorithm was implemented using Matlab and has been tested using a sample of various document images in various languages. The algorithm not only works for Hindi, Bengali, English and Tamil languages but for others as well. © Research India Publications.

International Journal of Applied Engineering Research

An algorithm for deskewing a document image

The development of high speed electronic devices tends to relevant changes in the designing of the converters for power applications mainly on the speed, size, reliability and efficiency. This paper proposes the hardware implementation of two level DC-DC boost converter. The proposed system has 12V - 48V boost converter with lamp loads by using dSPACE 1104 controller. Conventional DC-DC converters have the disadvantages of operating at high duty cycle, high switch voltage stress and high diode peak current. The major advantage of two level DC-DC boost converter are continuous input current, transformerless which allows high switching frequency and more levels can be added without modifying the main circuit. The two level DC-DC boost converter is validated by comparing simulation and hardware results under different duty ratio. © 2014 IEEE.

Department of Energy and Power Electronics

School of Electrical Engineering

2014 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)

12/48V two level DC-DC boost converter using DSPACE

The main key point of preferential image segmentation is to segment object of user interest based on intensities, boundaries and texture and ignoring the remaining portions. It utilizes a tree of shapes to represent the image content. This representation provides a hierarchical tree for the objects contained in the level sets of the image. The hierarchical structure is utilized to select the candidate objects from the image. The J-segmentation (J-SEG) provides a way to construct a tree of shapes. The boundaries of the selected objects are then compared with those of objects selected from prior images.