Papers by Manavalan Radhakrishnan
Diagnosing Prostate cancer is a challenging task for Urologists, Radiologists, and Oncologists. U... more Diagnosing Prostate cancer is a challenging task for Urologists, Radiologists, and Oncologists. Ultrasound imaging is one of the hopeful techniques used for early detection of prostate cancer. The Region of interest (ROI) is identified by different methods after preprocessing. In this paper, DBSCAN clustering with morphological operators is used to extort the prostate region. The evaluation of texture features is important for several image processing applications. The performance of the features extracted from the various texture methods such as histogram, Gray Level Cooccurrence Matrix (GLCM), Gray-Level Run-Length Matrix (GRLM), are analyzed separately. In this paper, it is proposed to combine histogram, GLRLM and GLCM in order to study the performance. The Support Vector Machine (SVM) is adopted to classify the extracted features into benign or malignant. The performance of texture methods are evaluated using various statistical parameters such as sensitivity, specificity and accuracy. The comparative analysis has been performed over 5500 digitized TRUS images of prostate.
Current Chinese Engineering Science, 2020
Neurological disorders, such as ALS, Alzheimer’s, epilepsy, Parkinson’s Disease, Autism, Atrial F... more Neurological disorders, such as ALS, Alzheimer’s, epilepsy, Parkinson’s Disease, Autism, Atrial Fibrillation, and Sclerosis, affect the central nervous system, including the brain, nerves, spinal cords, muscles, and Neuromuscular joint. These disorders are investigated by detecting the genetic variations in Single Nucleotide Polymorphism (SNP) in Genome-Wide Association Studies (GWAS). In the human genome sequence, one SNP influences the effects of another SNP. These SNP-SNP interactions or Gene-Gene interaction (Epistasis) significantly increase the risk of disease susceptibility to neurological disorders. The manual analyses of various genetic interactions related to neurological diseases are cumbersome. Hence, the computational system is effective for the discovery of Epistasis effects in neurological syndromes. This study aims to explore various techniques of statistical, machine learning, optimization so far applied to find the epistasis effect for neurological disorders. This ...
Human interface is vital individuality of group social dynamics in conference. The order of human... more Human interface is vital individuality of group social dynamics in conference. The order of human interaction is generally represented as a tree. Tree structure is used to capture how the person interacts in meetings and to find out the interactions. The human interaction are offering as an thought, giving comments, ask opinion, acknowledge, etc., Frequent interaction tree pattern mining algorithm and Frequent interaction sub tree pattern mining algorithm are utilized to analysis the structure and to extract interaction flow patterns, where co-occurring only the tags are considered. To conquer this problem, Sentiment Analysis (SA) is proposed work to the entire flow of interaction in meetings. A sentiment analysis approach extracts sentiments associated with opinions of positive or negative for specific subjects from the Tamil document instead of classifying the whole Tamil document into positive or negative. Sentiment analysis approach identifies the semantic relationship between t...
BoletÃn de la Asociación Médica de Puerto Rico, 1984
ArXiv, 2013
Stemming is the process of extracting root word from the given inflection word and also plays sig... more Stemming is the process of extracting root word from the given inflection word and also plays significant role in numerous application of Natural Language Processing (NLP). Tamil Language raises several challenges to NLP, since it has rich morphological patterns than other languages. The rule based approach light-stemmer is proposed in this paper, to find stem word for given inflection Tamil word. The performance of proposed approach is compared to a rule based suffix removal stemmer based on correctly and incorrectly predicted. The experimental result clearly show that the proposed approach light stemmer for Tamil language perform better than suffix removal stemmer and also more effective in Information Retrieval System (IRS).
International Journal of Intelligent Engineering Informatics, 2020
ArXiv, 2013
Stemming is the process of extracting root word from the given inflection word. It also plays sig... more Stemming is the process of extracting root word from the given inflection word. It also plays significant role in numerous application of Natural Language Processing (NLP). The stemming problem has addressed in many contexts and by researchers in many disciplines. This expository paper presents survey of some of the latest developments on stemming algorithms in data mining and also presents with some of the solutions for various Indian language stemming algorithms along with the results.
Int. Arab J. Inf. Technol., 2016
B rain tumor is one of the foremost causes for the increase in mortality among children and adult... more B rain tumor is one of the foremost causes for the increase in mortality among children and adults. Computer visions are being used by doctors to analysis and diagnose the medical problems. Magnetic Resonance Imaging (MRI) is a medical imaging technique, which is used to visualize internal structures of MRI brain images for analyzing normal and abnormal prototypes of brain while diagnosing. It is a non"invasive method to take picture of brain and the surrounding images. Image processing techniques are used to extract meaningful information from medical images for the purpose of diagnosis and prognosis. Raw MRI brain images are not suitable for processing and analysis since noise and low contrast affect the quality of the MRI images. The classification of MRI brain images is emphasized in this paper for cancer diagnosis. It can consist of four steps: Pre"processing, identification of region of interest, feature extraction and classification. For improving quality of the ima...
Medical & Biological Engineering & Computing
Genome-wide association studies (GWAS) provide clear insight into understanding genetic variation... more Genome-wide association studies (GWAS) provide clear insight into understanding genetic variations and environmental influences responsible for various human diseases. Cancer identification through genetic interactions (epistasis) is one of the significant ongoing researches in GWAS. The growth of the cancer cell emerges from multi-locus as well as complex genetic interaction. It is impractical for the physician to detect cancer via manual examination of SNPs interaction. Due to its importance, several computational approaches have been modeled to infer epistasis effects. This article includes a comprehensive and multifaceted review of all relevant genetic studies published between 2001 and 2020. In this contemporary review, various computational methods are as follows: multifactor dimensionality reduction-based approaches, statistical strategies, machine learning, and optimization-based techniques are carefully reviewed and presented with their evaluation results. Moreover, these computational approaches' strengths and limitations are described. The issues behind the computational methods for identifying the cancer disease through genetic interactions and the various evaluation parameters used by researchers have been analyzed. This review is highly beneficial for researchers and medical professionals to learn techniques adapted to discover the epistasis and aids to design novel automatic epistasis detection systems with strong robustness and maximum efficiency to address the different research problems in finding practical solutions effectively.
Computers and Electronics in Agriculture
Soft Computing, 2014
Ultrasound imaging is the most suitable method for early detection of prostate cancer. It is very... more Ultrasound imaging is the most suitable method for early detection of prostate cancer. It is very difficult to distinguish benign and malignant nature of the affliction in the early stage of cancer. This is reflected in the high percentage of unnecessary biopsies that are performed and many deaths caused by late detection or misdiagnosis. A computer based classification system can provide a second opinion to the radiologists. Generally, objects are described in terms of a set of measurable features in pattern recognition. The selection and quality of the features representing each pattern will have a considerable bearing on the success of subsequent pattern classification. Feature selection is a process of selecting the most wanted or dominating features set from the original features set in order to reduce the cost of data visualization and increasing classification efficiency and accuracy. The region of interest (ROI) is identified from transrectal ultrasound (TRUS) images using DBSCAN clustering with morphological operators after image enhancement using M3-filter. Then the 22 grey level co-occurrence matrix features are extracted from the ROIs. Soft computing model based feature selection algorithms genetic algorithm (GA), ant colony optimization (ACO) and QR are studied. In this paper, QR-ACO (hybridization of rough set based QR and ACO) and GA-ACO (hybridization GA and ACO) are proposed for reducing feature set in order to increase the accuracy and efficiency of the classification with regard to prostate cancer. The selected features may have the best discriminatory power for classifying prostate cancer based on TRUS images. Support vector machine is tailored for evaluation of the proposed feature selection methods through classification. Then, the comparative analysis is performed among these methods. Experimental results show that the proposed method QR-ACO produces significant results. Number of features selected using QR-ACO algorithm is minimal, is successful and has high detection accuracy.
Diagnosing Prostate cancer is a challenging task for Urologists, Radiologists, and Oncologists. U... more Diagnosing Prostate cancer is a challenging task for Urologists, Radiologists, and Oncologists. Ultrasound imaging is one of the hopeful techniques used for early detection of prostate cancer. The Region of interest (ROI) is identified by different methods after preprocessing. In this paper, DBSCAN clustering with morphological operators is used to extort the prostate region. The evaluation of texture features is important for several image processing applications. The performance of the features extracted from the various texture methods such as histogram, Gray Level Cooccurrence Matrix (GLCM), Gray-Level RunLength Matrix (GRLM), are analyzed separately. In this paper, it is proposed to combine histogram, GLRLM and GLCM in order to study the performance. The Support Vector Machine (SVM) is adopted to classify the extracted features into benign or malignant. The performance of texture methods are evaluated using various statistical parameters such as sensitivity, specificity and acc...
Human-centric Computing and Information Sciences, Apr 30, 2015
The objective of this study is to assess the combined performance of textural and morphological f... more The objective of this study is to assess the combined performance of textural and morphological features for the detection and diagnosis of breast masses in ultrasound images. We have extracted a total of forty four features using textural and morphological techniques. Support vector machine (SVM) classifier is used to discriminate the tumors into benign or malignant. The performance of individual as well as combined features are assessed using accuracy(Ac), sensitivity(Se), specificity(Sp), Matthews correlation coefficient(MCC) and area A Z under receiver operating characteristics curve. The individual features produced classification accuracy in the range of 61.66% and 90.83% and when features from each category are combined, the accuracy is improved in the range of 79.16% and 95.83%. Moreover, the combination of gray level co-occurrence matrix (GLCM) and ratio of perimeters (P ratio) presented highest performance among all feature combinations (Ac 95.85%, Se 96%, Sp 91.46%, MCC 0.9146 and A Z 0.9444).The results indicated that the discrimination performance of a computer aided breast cancer diagnosis system increases when textural and morphological features are combined.
Current Biotechnology
Background: The diseases in heart and blood vessels such as heart attack, Coronary Artery Disease... more Background: The diseases in heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include Gender, Age, Cholesterol/LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome Wide Association Studies (GWAS) focuses extremely on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infers the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular dis...
International Journal of Computational & Neural Engineering
Volume 6: Issue 1 by Manavalan Radhakrishnan
SciDoc Publishers, 2020
Agriculture plays a significant role in the growth of human civilization. The fruits and vegetabl... more Agriculture plays a significant role in the growth of human civilization. The fruits and vegetables are an important ingredient in the regular diets of the human. They provide high sources of vitamins and minerals that allow us to remain healthy. Citrus is used as a major source of nutrients along with vitamin C worldwide. The Citrus family consists of grapes, grapefruits, orange and lemons. The Plant diseases highly decline the growth of citrus fruits, creating a significant economic loss in agriculture. The identification of the citrus fruits leaves diseases in naked eyes leads to inaccurate results for the control measurements of pesticides. Hence, early diagnosis of diseases in citrus fruit automatically is necessary to increase the productivity. Image processing techniques are generally used to design a diagnosis system for extracting the features from the citrus plant images and identify the types of diseases at the early stage itself. This paper exhibits survey on different image processing techniques and machine learning approaches used to extract and quick examination of various citrus fruits like lemon, orange, and grapes leaves. The issues faced by the computational approaches for analyzing citrus fruits leaves are also given with future directions.
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Papers by Manavalan Radhakrishnan
Volume 6: Issue 1 by Manavalan Radhakrishnan