Mahua Bhattacharya

Mahua Bhattacharya
ABV-Indian Institute of Information Technology and Management Gwalior | IIITM · M.Tech Program in Information Communication Technology (ICT)

Professor(Full) B.Tech (Radio Physics & Electronics ) M.Tech (RPE) Ph.D.(Tech.) Univ. of Calcutta & Research carried out at-Indian Statistical Institute Calcutta

About

200
Publications
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Introduction
I am a Professor ( Full.) at ABV Indian Institute of Information Technology & Management (Govt of India, MHRD) , department of ICT . Ph.D. guidance 9 ; M.Tech scholar 100+ , Govt funded project completed and undergoing :6, Academic Abroad visit in countries - Bulgaria, USA, UK, Hongkong. Germany. Area:: Medical image processing, expert system design for agriculture, , Editorial Board member Neural Computing and Applications, (2016-18) Springer. President- International Neural Network Society, Indian Chapter 2016 onward.

Publications

Publications (200)
Article
Full-text available
Different deep learning-based architectures have been developed for medical image registration in the last few years. The architectures of these methods are complex and require a considerable amount of memory. The scalability of the architectures is limited due to their compatibility with low or moderate memory devices. The deformable image registr...
Article
Full-text available
The automated and accurate detection of brain tumors is challenging for classifying brain Magnetic Resonance (MR) images. The conventional techniques for diagnosing the images are tedious and inefficient in decision making. Therefore, this work proposes an adaptive and non-invasive method for accurately classifying images into pathological and norm...
Article
Full-text available
In the automated diagnosis of breast cancer (BC), microscopic images based on multi‐classification play a prominent role. Multi‐classification of BC means to differentiate among the sub‐categories of BC (papillary carcinoma, ductal carcinoma, fibroadenoma, etc.). However, unpretentious contrasts in various sub‐categories of BC occur due to the wide...
Conference Paper
Abstract: Extraction from large no. of features (genes signatures) are the major issues in the prediction of cancer and its specific type identification using microarray datasets. Even though most classifiers predict the class (normal or cancerous) for various cancers, the accuracy of prediction still suffers. This is due to the importance of fewer...
Article
Nowadays, the demand for the Industrial Internet of Things (IIoT) technology has increased immensely in various fields such as the agriculture industry, smart mines, smart factories, the healthcare industry, etc. Industrial Wireless Sensor Networks (IWSNs) act as a backbone of any IIoT system by forming a network of heterogeneous sensors. In IWSNs...
Article
Full-text available
Brain abnormalities are neurological disorders of the human nervous system that contain biochemical, electrical, and structural changes in the brain and spinal cord. However, such changes produce diverse symptoms like paralysis, amnesia, and muscle weakness. The diagnosis of these abnormalities is crucial for treatment planning in the early stage t...
Article
Full-text available
This work proposes a novel region-estimation (RE) algorithm using the quantification of colon-cancer (HCT-8) and fibroblasts (NIH3T3) cells to estimate the densest region of colon-cancer cells in in vitro 3D co-cultured spheroids. Cells were labelled with different cell tracker dyes to track the cells. The technique involves staining cells with cel...
Article
Full-text available
Diagnosis of lymph node metastases is a challenging task for pathologists, involving an extensive screening of the pathological scans. Automating diagnostic processes reduces the workload of pathologists and yields high accuracy by the virtue of advances in technology. In this study, a novel ensemble-based framework is proposed for the classificati...
Article
Recently, Internet of Things (IoT) has attracted much interest in its wide applications such as smart healthcare, home automation, transportation, and smart city. In these IoT-based systems, Wireless Sensor Networks (WSNs) are highly used to gather information needed by smart environments. However, due to huge heterogeneous data coming from differe...
Chapter
In recent research, breast cancer has come out to be the biggest reason behind death among females. Detection of breast cancer in its earlier stages is really the need of time. Detection of cancerous tumors is really a long and time taking process which is very costly and requires a lot of workforces as well. Therefore, providing CAD for simpler cl...
Conference Paper
Full-text available
In recent days most digital imaging devices i.e. the high resolution images or videos are playing a critical role in the areas of image processing and application. They too are becoming helpful in the areas of medical diagnosis. This type of images is basically helpful in the pictorial information of human understanding. The algorithm of single ima...
Chapter
Cancer is a critical general medical issue on the human race today. As per the World Health Organizations (WHO) International Agency for Research on Cancer, the world has already witnessed 8.2 million passing as a result of malignancy in 2012 and these numbers could reach up to 27 million before 2030. Especially, breast cancer is the main source of...
Poster
Full-text available
Cell-to-cell interaction in tumor is mainly influenced by extracellular microenvironment. Confocal mi-croscopy technique is one of the well-known imaging techniques to understand cell-to-cell interaction in different focal planes. However, rapid and accurate evaluation of those images is in urgent need. To achieve this, Squirrel Search Algorithm (S...
Conference Paper
Full-text available
This work was done in the Ph D program of Ph D scholar Arpita Das under the guidance of Prof. Mahua Bhattacharya as one of objective of the PhD objective proposal and also a part of Biomedical Image Processing Research.
Article
Wireless Sensor Networks (WSNs) is the key element of the Internet of Things (IoT) for sensing the environment, collecting data and sending it to the base station (BS). In the IoT environment, routing protocols that are designed for WSNs are not working properly due to heterogeneity in the nodes. Therefore, an intelligent based routing protocol is...
Article
The segmentation and classification of brain magnetic resonance (MR) images are the crucial and challenging task for radiologists. The conventional methods for analyzing brain images are time-consuming and ineffective in decision-making. Thus, to overcome these limitations, this work proposes an automated and robust computer-aided diagnosis (CAD) s...
Article
The automatic cell analysis method is capable of segmenting the cells and can detect the number of live/dead cells present in the body. This study proposed a novel non-linear segmentation model (NSM) for the segmentation and quantification of live/dead cells present in the body. This work also reveals the aspects of electromagnetic radiation on the...
Conference Paper
The wireless sensor networks are formed from the network of sensors capable of sensing the physical phenomenon around like heat, light, motion, temperature, humidity, pressure etc. Sensors are tiny shape and deployed in mostly remote areas. The journey of data in the form of packets from the sensor mote to sink underwent many challenges. Huge resea...
Conference Paper
Automatic analysis of histopathology specimens images can be utilized in early extraction and detection of diseases such brain tumor, breast malignancy, colon cancer etc. The early detection of cancer may allow patients to take proper treatment. In this paper, an automatic cell nuclei segmentation based on deep learning strategies using 2-D histolo...
Poster
Abstract: Cell-to-cell interaction in tumor is mainly influenced by extracellular microenvironment. Confocal mi- croscopy technique is one of the well-known imaging techniques to understand cell-to-cell interaction in different focal planes. However, rapid and accurate evaluation of those images is in urgent need. To achieve this, Squirrel Search A...
Conference Paper
In the area of clustering, the most common issue of obtaining the optimum number value for the clusters is still an open challenge for different application areas. It is very hard to get the optimal number of clusters because of the lack of prior knowledge. This happens due to having various dimensions of data, clusters having a wide range of shape...
Conference Paper
Inspite the many significant researches has been done in the area of neurological field based on detection and extraction of morphology of the dendritic spines. Still the current researches and automated tools have various shortcomings against the detection and analysis of the dendritic spines. The detection and extraction of neuronal morphology of...
Article
Robust segmentation of the brain magnetic resonance (MR) images is extremely important for diagnosing the tissues quantitatively. It is crucial to detect the changes caused by the growth of edema and tumor in healthy tissues for better medical treatment planning. In order to increase the image quality, skull stripping or brain extraction is an esse...
Conference Paper
In 3D cancer cell spheroids, particularly in vitro co-culture techniques, there is an urgent need in a vivid understanding of the interaction of cancer cells with the counter stromal cells. Fluorescence imaging and confocal microscopy techniques will aid in imaging the cells, and it is required the easiest and fast approach in identifying the inter...
Conference Paper
In 3D cancer cell spheroids, particularly in vitro co-culture techniques there is an urgent need in vivid understanding of the interaction of cancer cells with the counter stromal cells. Fluorescence imaging and confocal microscopy techniques will aid in imaging the cells, and it is required an easiest and fast approach in identifying the interacti...
Conference Paper
Nissl Stained Rat Brain Cell Image Analysis Post Exposure to Electromagnetic Fields Using Image Processing Techniques Bhakti Netke, Swati Dongre, Nalini Bhadouria and Mahua Bhattacharya ABV-Indian Institute of Information Technology, Gwalior email: bhakti.1995@gmail.com, swati.k.dongre@gmail.com Abstract— Studies have shown that mobile phones whic...
Article
Full-text available
Various studies on interest point (IP) detection have concluded that maximally stable extremal region (MSER)-based IPs outperform others on repeatability, localization accuracy, robustness, efficiency and covariance to global and local image distortions. Since medical images lack sharp detail, corner IPs are not a suitable choice for them. Instead,...
Conference Paper
Segmentation of brain tumor from magnetic resonance imaging is a time consuming and critical task due to unpredictable characteristics of tumor tissues. In this paper, we propose a new tissue segmentation algorithm that segments brain MR images into gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), tumor and edema. It is crucial to se...
Conference Paper
Automated cell nuclei determination of stained images is of uttermost importance for diagnosis. In this work, we have proposed a novel efficient and accurate image segmentation technique for densely clustered overlapping cell nuclei. Firstly, we have extracted the cell body (foreground) from the background using global thresholding followed by loca...
Conference Paper
In this paper we have presented an automated diagnosis of breast cell cancer using histopathological images on the basis of different textural descriptors. In the proposed technique, the images being preprocessed using extended adaptive-top-bottom transform (E AHE -TB hat ) and segmented the nuclei regions from the non-nuclei regions using region g...
Chapter
Automated cell nuclei determination of stained images is of uttermost importance for diagnosis. In this work, we have proposed a novel efficient and accurate image segmentation technique for densely clustered overlapping cell nuclei. Firstly, we have extracted the cell body (foreground) from the background using global thresholding followed by loca...
Chapter
The proposed chapter describes the need of data security and content protection in the modern health care system. A digital watermarking technique is used as a strong and secure tool to achieve ultimate security. In this chapter the authors discuss some existing watermarking techniques and also describe some new types of data hiding techniques usin...
Article
Full-text available
Organizing data into sensible groups is called as ‘data clustering.’ It is an open research problem in various scientific fields. Neither a universal solution nor an absolute strategy for its evaluation exists in the literature. In this context, through this paper, we make following three contributions: (1) A new method for finding ‘natural groupin...
Article
Full-text available
The medical imaging can be divided into two global categories: anatomical and functional. Anatomical modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging and ultrasound primarily describe the structural morphology of the object. Few other techniques such as electroencephalography, magneto encephalography, Positron emissio...
Article
The density based notion for clustering approach is used widely due to its easy implementation and ability to detect arbitrary shaped clusters in the presence of noisy data points without requiring prior knowledge of the number of clusters to be identified. Density-based spatial clustering of applications with noise (DBSCAN) is the first algorithm...
Article
Full-text available
Ad hoc method for segmentation of mature or nearly mature cotton bolls is proposed based on proper feature vector selection and efficient application of Fuzzy c-means (FCM) on images. Perception of color is used as fundamental criteria for segmentation. The results obtained are compared with conventional FCM and supremacy of the proposed work is pr...
Article
Image registration is an ill-posed problem. But due to the fact that it finds applications in many fields, it is an open research area. There are many ways to register images of which interpolation-based image registration is widely used. The accuracy of interpolation-based image registration depends largely on two factors - (1) Accurate localizati...
Conference Paper
PCNN Model is widely used because it simulates the working of visual cortex in cats, but parameter setting in PCNN is hefty affair because of manual adjusting of many initial parameters. Through this paper, we present an efficient optimization approach to reducing the parameter setting in original PCNN model by changing the threshold function to mo...
Conference Paper
Histogram based multilevel thresholding is one of the most aggressive methods to realize image segmentation. We have used histogram based multilevel thresholding as a gray image applying Firefly and social spider algorithm. For thresholding, we have worked on Kapur's and Otsu's methods to maximize the objective function values. We have used standar...
Chapter
Abstract Multi-level based thresholding is one of the most imperative techniques to realize image segmentation. In order to determine the threshold values automatically, approaches based on histogram are commonly employed. We have deployed histogram based bi-modal and multi-modal thresholding for gray image using social spider algorithm (SSA). We...
Chapter
Image processing and recognition is a modern field which is gaining popularity due to its capability to automate certain mundane object recognition tasks and provide unparalleled accuracy and precision. Computer graphics have evolved sufficiently so as to cater to a wide array of applications ranging from categorizing mechanical parts of a machine...
Conference Paper
Multi-Robot system became an important research area in the Robotics and Artificial Intelligence. In the presence of obstacles, uncertainty and incomplete information Multi-Robot system is used to accomplish the task in more efficient way as compared to single robot system. Navigation of robots in its surrounding is essential to avoid unacceptable...
Conference Paper
Wavelength division multiplexing allow the multiple channel to transmit the data at high speed at the same instant. For large distance communication, Single mode fiber is preferred over Multimode fiber. Quality factor decreases as data rate and optical fiber length increases. In this proposed work Optisystem 13.0 simulator is used to analyze disper...
Chapter
Chenvese() is the perform used to utilize the Chan-vese calculation for the count of divided depiction. The capacity has 3 contentions. The main contention is the pre-prepared photo. The second contention is the measurements of the preparatory veil. The 1/3 contention is the amount of cycles, on every era the cover measurement increments. After we...
Chapter
Multi-level based thresholding is one of the most imperative techniques to realize image segmentation. In order to determine the threshold values automatically, approaches based on histogram are commonly employed. We have deployed histogram based bi-modal and multi-modal thresholding for gray image using social spider algorithm (SSA). We have emplo...
Conference Paper
We present seeded region growing algorithm using notion of ‘affinity’ as region growth mechanism for segmentation of medical images. Affinity between pair of pixels captures the idea of nearness in location and similarity between their gray scale values. Affinity has the capability to separate different segments of the images depending upon its fun...
Conference Paper
We present seeded region growing algorithm using notion of ‘affinity’ as region growth mechanism for segmentation of medical images. Affinity between pair of pixels captures the idea of nearness in location and similarity between their gray scale values. Affinity has the capability to separate different segments of the images depending upon its fun...
Conference Paper
Entire brain consists of several tissues specifically gray matter (GM), white matter (WM) and cerebrospinal fluid CSF. From brain image it is troublesome to delineate these tissue regions exclusively since these regions are not well defined by sharp boundaries. In present paper a combination of approaches namely bias-field corrected fuzzy C-means a...
Conference Paper
Current paper represents a new type of encrypted Electronic Patient Record (EPR) code used for data encryption and content protection. EPR is a collection of several private information related to a patient which needs data authenticity, data security as well as safe and secured transmission. The proposed methodology used both cryptography and imag...
Conference Paper
In this paper we have proposed an effective fusion method to combine the information of brain MRI and PET images to study Alzheimer's disease of the patients. The proposed methodology is applied to the wavelet based multi-scale image fusion algorithm. In this method principal component analysis (PCA) approach for integrating each RGB component of a...
Conference Paper
There are many methods to find Interest Points (IPs) in images for image registration. However, the underlying heuristics for finding them is different for each. Due to this, their behavior towards different image distortions is expected to vary. Through this paper, we attempt to investigate the truth of the following hypothesis ??? "Global Transfo...
Conference Paper
Full-text available
The correlation between the environmental features and image features of cotton boils is the necessary step for the pattern recognition and translate those features for machine understanding is the main challenge to distinguish mature cotton boil from immature one. Present work is tried to solve this problem using shape based features. The fuzzy ba...
Conference Paper
Full-text available
Ad-hoc method for segmentation of mature or nearly mature cotton bolls is proposed based on proper feature vector selection and efficient application of Fuzzy c means (FCM) on images. Perception of color is used as fundamental criteria for segmentation. The results obtained are compared with conventional FCM and supremacy of the proposed work is pr...
Conference Paper
Full-text available
Abstract. Image Segmentation is an open research area in which Multilevel thresholding is a topic of current research. To automatically detect the threshold, histogram based methods are commonly used. In this paper, histogram based bi-level and multi-level segmentation is proposed for gray scale image using spider monkey optimization (SMO). In or...
Conference Paper
Full-text available
Abstract--In recent days most digital imaging devices i.e. the high resolution images or videos are playing a critical role in the areas of image processing and application. They too are becoming helpful in the areas of medical diagnosis. This type of images is basically helpful in the pictorial information of human understanding. The algorithm of...
Article
Full-text available
The medical imaging can be divided into two global categories: anatomical and functional. Anatomical modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging and ultrasound primarily describe the structural morphology of the object. Few other techniques such as electroencephalography, magneto encephalography, Positron emissio...
Article
Full-text available
Clustering high dimensional dataset is one of the major areas of research because of its widespread applications in many domains. However, a meaningful clustering in high dimensional dataset is a challenging issue due to (i) it usually contains many irrelevant dimensions which hide the clusters, (ii) the distance, which is the most common similarit...
Article
Full-text available
Clustering high dimensional dataset is one of the major areas of research because of its widespread applications in many domains. However, a meaningful clustering in high dimensional dataset is a challenging issue due to (i) it usually contains many irrelevant dimensions which hide the clusters, (ii) the distance, which is the most common similarit...
Article
Full-text available
Image Segmentation is an open research area in which Multi-level thresholding is a topic of current research. To automatically detect the threshold, histogram-based methods are commonly used. In this paper, histogram-based bi-level and multi-level segmentation are proposed for gray scale image using spider monkey optimization (SMO). In order to max...
Conference Paper
Steganography is a concept of hiding information in order for data to remain safe and unhandled by eve droppers. In this paper we are demonstrating a way to transmit data from sender to receiver without being handled by eve through a new technique of steganograpy. We are using an audio file for hiding our data as audio are very less judged to chang...