Surya Prasath

Surya Prasath
Cincinnati Children's Hospital Medical Center | CCHMC · Division of Biomedical Informatics

PhD
For collaborative works contact at surya.iit@gmail.com and see our AI Lab for more details: https://www.prasathlab.com

About

216
Publications
86,414
Reads
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2,392
Citations
Introduction
Applied Mathematician with substantial knowledge in AI, image processing, computer vision, machine learning, and data science. Also work on a variety of other problems that are mathematically interesting and fun to do. Always looking forward to do collaborative work and interested in making connections in different data science areas. Contact me at surya.iit@gmail.com More details: http://prasathlab.com/
Additional affiliations
June 2018 - present
University of Cincinnati
Position
  • Professor (Assistant)
March 2018 - present
Cincinnati Children's Hospital Medical Center
Position
  • Professor (Assistant)
March 2018 - present
University of Cincinnati
Position
  • Professor (Assistant)
Education
August 2004 - November 2009
Indian Institute of Technology Madras
Field of study
  • Mathematics
August 2002 - May 2004
Indian Institute of Technology Madras
Field of study
  • Mathematics

Publications

Publications (216)
Preprint
Full-text available
Federated learning (FL) is a system in which a central aggregator coordinates the efforts of multiple clients to solve machine learning problems. This setting allows training data to be dispersed in order to protect privacy. The purpose of this paper is to provide an overview of FL systems with a focus on healthcare. FL is evaluated here based on i...
Book
This book was created with the intention of informing an international audience about the latest technological aspects for developing smart agricultural applications. As artificial intelligence (AI) takes the main role in this, the majority of the chapters are associated with the role of AI and data analytics components for better agricultural appl...
Article
Full-text available
Image registration is a critical component in the applications of various medical image analyses. In recent years, there has been a tremendous surge in the development of deep learning (DL)-based medical image registration models. This paper provides a comprehensive review of medical image registration. Firstly, a discussion is provided for supervi...
Preprint
Full-text available
Image registration is a critical component in the applications of various medical image analyses. In recent years, there has been a tremendous surge in the development of deep learning (DL)-based medical image registration models. This paper provides a comprehensive review of medical image registration. Firstly, a discussion is provided for supervi...
Article
Full-text available
Federated learning (FL) refers to a system in which a central aggregator coordinates the efforts of several clients to solve the issues of machine learning. This setting allows the training data to be dispersed in order to protect the privacy of each device. This paper provides an overview of federated learning systems, with a focus on healthcare....
Preprint
Full-text available
Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns f...
Article
Full-text available
Dementia is one of the leading causes of severe cognitive decline, it induces memory loss and impairs the daily life of millions of people worldwide. In this work, we consider the classification of dementia using magnetic resonance (MR) imaging and clinical data with machine learning models. We adapt univariate feature selection in the MR data pre-...
Article
Full-text available
The human lung is a complex organ with high cellular heterogeneity, and its development and maintenance require interactive gene networks and dynamic cross-talk among multiple cell types. We focus on the confocal immunofluorescent (IF) images of lung tissues from the LungMAP database to reveal lung development. Using the current state-of-the-art de...
Conference Paper
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The emphasis of this article is on the data-driven diagnosis of polycystic ovary syndrome (PCOS) in women. Data from the Kaggle repository is used to train ensemble machine learning algorithms. There are 177 women with PCOS in this dataset, which includes 43 different characteristics. To begin, a univariate feature selection and feature elimination...
Preprint
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Transcription factors read the genome, fundamentally connecting DNA sequence to gene expression across diverse cell types. Determining how, where, and when TFs bind chromatin will advance our understanding of gene regulatory networks and cellular behavior. The 2017 ENCODE-DREAM in vivo Transcription-Factor Binding Site (TFBS) Prediction Challenge h...
Article
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In this paper, we present an efficient dermoscopic image segmentation method based on the linearisation of gamma-correction, and convolutional neural networks. Linearisation of gamma-correction is helpful to enhance low-intensity regions of skin lesion areas. Therefore, postprocessing tasks can work more effectively. The proposed convolutional neur...
Preprint
Full-text available
An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a gateway portal. This portal connects a bro...
Article
Full-text available
Image denoising methods are of fundamental importance in image processing and artificial intelligence systems. In this review, we analyze the traditional and state of the art mathematical models for computational color image denoising. These algorithms are divided into methods that are based on the partial differential equations, low rank, sparse r...
Article
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Knowledge of the anatomy of each tissue and the relationships between progenitors and daughter cells is necessary to understand physiology and pathology. The anatomy of hematopoiesis in the marrow remains largely unknown. Here we identify strategies to image all steps of blood cell production in the mouse sternum using confocal microscopy. We show...
Article
Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiledpersons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully conne...
Preprint
Full-text available
Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiled-persons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully conn...
Preprint
Full-text available
Hundreds of bioinformatics approaches now exist to define cellular heterogeneity from single-cell genomics data. Reconciling conflicts between diverse methods, algorithm settings, annotations or modalities have the potential to clarify which populations are real and establish reusable reference atlases. Here, we present a customizable computational...
Article
Full-text available
Volume estimation of brain tissues such as the White Matter, Gray Matter and Cerebrospinal Fluid is an important task in brain image analysis and also used to diagnose neurological and psychiatric disorders. In this work, brain tissue volume reduction is estimated to detect Alzheimer’s disease (AD) using magnetic resonance images. The proposed meth...
Article
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Background In critically ill infants, the position of a peripherally inserted central catheter (PICC) must be confirmed frequently, as the tip may move from its original position and run the risk of hyperosmolar vascular damage or extravasation into surrounding spaces. Automated detection of PICC tip position holds great promise for alerting bedsid...
Preprint
Full-text available
The outbreak of novel coronavirus disease (COVID- 19) has claimed millions of lives and has affected all aspects of human life. This paper focuses on the application of deep learning (DL) models to medical imaging and drug discovery for managing COVID-19 disease. In this article, we detail various medical imaging-based studies such as X-rays and co...
Article
Full-text available
The outbreak of novel coronavirus disease (COVID-19) has claimed millions of lives and has affected all aspects of human life. This paper focuses on the application of deep learning (DL) models to medical imaging and drug discovery for managing COVID-19 disease. In this article, we detail various medical imaging-based studies such as X-rays and com...
Article
Full-text available
Having control over your data is a right and a duty that every citizen has in our digital society. It is often that users skip entire policies of applications or websites to save time and energy without realizing the potential sticky points in these policies. Due to obscure language and verbose explanations majority of users of hypermedia do not bo...
Article
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This paper focuses on the application of deep learning (DL) based model in the analysis of novel coronavirus disease (COVID-19) from X-ray images. The novelty of this work is in the development of a new DL algorithm termed as optimized residual network (CO-ResNet) for COVID-19. The proposed CO-ResNet is developed by applying hyperparameter tuning t...
Cover Page
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COVID-19 pandemic has significantly changed our lives. Countries are introducing social distancing measures, including lockdown, to avoid the spread of infection. Organisations are implementing new ways of continuing their business by facilitating work from home and avoiding contacts using the Internet of Medical Things (IoMT), Internet of Healthca...
Cover Page
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Agriculture is one of the most fundamental human activities. Agriculture is the key sector for any developing country. As our farming capacity has expanded, usage of resources such as land, fertilizer, and water have grown exponentially. In order to establish digital smart agriculture, artificial intelligence (AI) can play anaggressive role. This b...
Article
Full-text available
In this world of big data, the development and exploitation of medical technology is vastly increasing and especially in big biomedical imaging modalities available across medicine. At the same instant, acquisition, processing, storing and transmission of such huge medical data requires efficient and robust data compression models. Over the last 2...
Article
Full-text available
In the last two decades, incredible progress in various medical imaging modalities and sensing techniques have been made, leading to the proliferation of three-dimensional (3D) imagery. Byproduct of such great progress is the production of huge volume of medical images and this big data place a burden on automatic image processing methods for diagn...
Article
Full-text available
Cytolytic T-cells play an essential role in the adaptive immune system by seeking out, binding and killing cells that present foreign antigens on their surface. An improved understanding of T-cell immunity will greatly aid in the development of new cancer immunotherapies and vaccines for life-threatening pathogens. Central to the design of such tar...
Article
Full-text available
Image restoration with regularization models is very popular in the image processing literature. Total variation (TV) is one of the important edge preserving regularization models used, however, to obtain optimal restoration results the regularization parameter needs to be set appropriately. We propose here a new parameter estimation approach for t...
Article
Full-text available
We study a multiscale tensor regularization based JPEG decompression artifact removal in digital images. Structure tensor eigenvalues based robust edge map is used within a variable exponent regularization. Variational constrained minimization which combines data fidelity driven by color subsampling and discrete cosine transformation operator is ut...
Conference Paper
Full-text available
Background: Infants in the neonatal intensive care unit (NICU) frequently need peripherally inserted central catheters (PICC) to provide medications, parenteral nutrition, and fluids. An upper extremity PICC line tip is optimally positioned “centrally” in the superior vena cava (SVC) or at the SVC-right atrial (RA) junction. Malpositioned PICC lin...
Chapter
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We present a multiregion image segmentation approach which utilizes multiscale anisotropic diffusion based scale spaces. By combining powerful edge preserving anisotropic diffusion smoothing with isolevel set linking and merging, we obtain coherent segments which are tracked across multiple scales. A hierarchical tree representation of the given in...
Article
Full-text available
In contrast to nearly all other tissues, the anatomy of cell differentiation in the bone marrow remains unknown. This is owing to a lack of strategies for examining myelopoiesis—the differentiation of myeloid progenitors into a large variety of innate immune cells—in situ in the bone marrow. Such strategies are required to understand differentiatio...
Article
Full-text available
With the progress in technology innovations, business organizations have preferred usage of online trading instead of traditional ways of trading. Online stores let businessmen offer more variety of products without the need of having big warehouses. At the same time, online shopping also saves time of customers and let them enjoy buying-at-home ex...
Article
In the article, we propose a robust impulse denoising method based on noise accumulation and harmonic analysis techniques (NAHAT filter). Noise accumulation technique is used to improve the ability to detect noisy pixels, and a harmonic function is used to gain the accuracy of restoring gray values of the detected noisy pixels. The proposed method...
Article
Full-text available
Melanoma skin cancer is one of the most dangerous forms of skin cancer because it grows fast and causes most of the skin cancer deaths. Hence, early detection is a very important task to treat melanoma. In this article, we propose a skin lesion segmentation method for dermoscopic images based on the U-Net architecture with VGG-16 encoder and the se...
Article
Euler's Elastica is a common approach developed based on minimizing the elastica energy. It is one of the effective approaches to solve the image inpainting problem. Nevertheless, there are two major issues: the Euler's elastica variational image inpainting model itself is multiparameter, and the performance of methods for solving the model is not...
Chapter
Full-text available
In the current study, we focus on the development of a numerical algorithm for the Laplace equation-based image inpainting problem. A software program to implement the proposed algorithm is also developed. In experiments, the proposed method recovered corrupted images effectively. It can also remove defects as well as unnecessary objects successful...
Conference Paper
Full-text available
Image dehazing is an important problem and it is useful as a preprocessing step in various automatic image analysis systems. The goal of image dehazing is the quality improvement of digital images by removing haze across the scene. In the present work, we consider an automatic image dehazing approach that is based on optimal color channels and nonl...
Article
Full-text available
Pathology is an important field in modern medicine. In particular, the step of nuclei segmentation is an important step in cancer analysis, diagnosis, and grading because cancer analysis, diagnosis, classification, and grading are highly dependent on the quality (accuracy) of nuclei segmentation. In the conventional cancer diagnosis, pathologists a...
Chapter
Full-text available
In the era of wireless communication, internet devices such as smart phones, hotspots, and Wi-Fi zone are important player of rapid growth of data usage. Internet connection devices are building new challenges for internet service providers such as higher bandwidth and indomitable increasing users day to day. This article gives an overview of exist...
Article
Full-text available
T-cells play an essential role in the adaptive immune system by seeking out, binding and destroying foreign antigens presented on the cell surface of diseased cells. An improved understanding of T-cell immunity will greatly aid in the development of new cancer immunotherapies and vaccines for life threatening pathogens. Central to the design of suc...
Article
Full-text available
CNNを用いたGliomaの疾患進行度評価における形状特徴量に関する一検討 (Japanese title) Recently, a lot of studies using Deep Learning techniques have been reported in the field of Digital Histopathology. For instance, there are ideas using deep Convolutional Neural Network (CNN) for disease stage classification and segmentation. These methods are expected to reduce pathologists’...
Article
Full-text available
Information security using image steganography is the process of concealing secret information within an image. The conventional methods are static approaches having fixed capacity in term of embedding rate. To solve the problem of static behavior and fixed capacity, we proposed a method that is dynamic approach and increased capacity for embedding...
Article
Full-text available
The total variation (TV) regularization model for image restoration is widely utilized due to its edge preservation properties. Despite its advantages, the TV regularization can obtain spurious oscillations in flat regions of digital images and thus recent works advocate high-order TV regularization models. In this work, we propose an adaptive imag...
Article
Full-text available
Visualization of inner gastrointestinal (GI) tract is an important aspect in diagnosis of diseases such as the bleeding and colon cancer. Wireless capsule endoscopy (WCE) provides painless imaging of the GI tract without much discomfort to patients via near-lights imaging model and with burst light emitting diodes (LEDs). This imaging system is des...
Article
Full-text available
Image edge detection is an important task in image processing and pattern recognition. Edges in digital images signify image discontinuities and traditionally gradient information is utilized in finding possible edge pixels. In this work, we consider a fusion approach using multiscale gradient maps along with non-parametric Fisher information which...
Article
Full-text available
Image restoration is an important and interesting problem in the field of image processing because it improves the quality of input images, which facilitates postprocessing tasks. The salt-and-pepper noise has a simpler structure than other noises, such as Gaussian and Poisson noises, but is a very common type of noise caused by many electronic dev...
Chapter
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Tourism industry could be one of the largest sources of revenue for any country. After the emergence of Web 2.0, it is also one of the largest data intensive industries in the world. Tourism‐rich countries often use Tourism Information Systems (TIS) for management of tourism‐related data. These systems are used are used on several levels of tourism...
Article
Full-text available
We propose Adaptive Switching Weight Mean Filter (ASWMF) to remove the salt and pepper noise. Instead of using median or mean, ASWMF assigns value of a switching weight mean (SWM) to grey value of the centre pixel of an adaptive window. SWM is evaluated by eliminating all noisy pixels from the adaptive window and putting a low weight for pixels on...
Article
Full-text available
We propose a chest X-Ray image denoising method based on Total variation regularization with implementation on the Nesterov optimization method. The denoising problem is formulated in the form of the second-order cone programming problem and then it is transformed to a saddle point problem under the min-max form. The chest X-Ray images are also pro...
Article
Full-text available
The present communication is devoted to the construction of monotone difference schemes of the second order of local approximation on non-uniform grids in space for 2D quasi-linear parabolic convection-diffusion equation. With the help of difference maximum principle, two-sided estimates of the difference solution are established and an important a...
Article
Full-text available
We provide here an optimal method of approximating a signal by piecewise constant functions. To this end, we minimize over the signal subdomains a fidelity term between the signal and its corresponding piecewise approximations; subdomains being determined by the number of approximations samples used for. An optimal recursive relationship is then ob...
Article
Full-text available
According to statistics of the American Cancer Society, in 2015 there are about 91 270 American adults diagnosed with melanoma of the skin. For the European Union, there are over 90 000 new cases of melanoma annually. Although melanoma only accounts for about 1% of all skin cancers, it causes most of the skin cancer deaths. Melanoma is considered o...
Chapter
Full-text available
In this article, we study and propose an adaptive thresholding segmen-tation method for dermoscopic images with Gabor filters and Principal Component Analysis. The Gabor filters is used for extracting statistical features of image and the Principal Component Analysis is applied for transforming features to various bases. In experiments, we implemen...