Prajakta kale - Academia.edu (original) (raw)

Papers by Prajakta kale

International Journal of Pharmaceutical Research, Feb 2, 2021

Growing advancements in automation industry have paved a way for medicine domain in terms of CAD ... more Growing advancements in automation industry have paved a way for medicine domain in terms of CAD system as an aid for health practitioners. Lung cancer is one such disease where accuracy and aid are of utmost important for proper diagnosis and enhanced survival rate. In the following comprehensive study, we aim at developing a Computer Aided Diagnostic System for detecting the lung cancer in the patient based on the Computed Tomography scan along with the predicting the stage of lung cancer. The proposed model is based upon the two-dimensional Convolutional Neural Networks with accuracies of 99% and 98% respectively for both the stages-detection and prediction. In future we aim at developing this system for other types of cancers.

with the latest technical developments in healthcare, the emphasis has always been upon improving... more with the latest technical developments in healthcare, the emphasis has always been upon improving existing systems' speed and accuracy. Increasing survival rate of the patient from lung malignance is one of such challenge which interests researchers. lung cancer survival rate of patients depends upon the stage in which the cancer is detected. If detected in early (first) stage, there are more chances of the diseases to be cured and the survival chances of the patient are more than 50%. This requires the advanced analysis because the symptoms normally overlap with other lung diseases. CT scan images are widely used all over the world for this analysis. Image processing contributes significantly in analysis of the CT scan images. This paper sheds light on current literature strategies, with thorough studies of each phase. A comparative analysis has been presented. Final steps for the detection of lung cancer are then proposed based on the conclusions of the analysis.

The overlapping symptoms of lung cancer with other pulmonary diseases is one of the critical reas... more The overlapping symptoms of lung cancer with other pulmonary diseases is one of the critical reasons that makes it difficult to differentiate the lung nodule as cancerous or noncancerous. Computed Aided Design (CAD) systems are rigorously researched for enhancing the accuracy of the model to predict the nature of the detected nodule. The differentiation of a lung nodule into cancer or non-cancer, and nature as benign or malignant, are important aspects of analysis. The increasing use of technologies like deep learning and neural networks has proven to be the drivers of 12st century in all the domains of research. In the comprehensive study, we present a two-dimensional convolutional neural network for predicting the nodule. The accuracy of the presented model is 99% with the split ratio of the training into the ratio of 0.7:0.1:0.1.

Image segmentation is the crucial step in a Computer-aided diagnostic system. The recent advancem... more Image segmentation is the crucial step in a Computer-aided diagnostic system. The recent advancements in technological ways have explored all the possible ways of segmenting images, especially in lung cancer area to enhance accuracy with reduced time and complexity. In this study, we present a lung segmentation model on the basis of morphological functions which is used further for classification step. The accuracy with the proposed segmentation is achieved as 99% for binary classification of the lung image into benign and malignant. The method will be explored further to use it for other types of cancers.

Lung cancer holds the highest position in the list of reasons for deaths in the world. The limita... more Lung cancer holds the highest position in the list of reasons for deaths in the world. The limitations of most of the Computer Aided Design Systems is that they just predict the whether the given image is cancerous or non-cancerous. It is equally important to study how to detect the stage of the cancer from the extracted nodule. In this paper, we present a comparative analysis of the literature survey in terms of stage classification of lung cancer. The latest research trends are explored presenting their accuracies as well as limitations.

Growing advancements in automation industry have paved a way for medicine domain in terms of CAD ... more Growing advancements in automation industry have paved a way for medicine domain in terms of CAD system as an aid for health practitioners. Lung cancer is one such disease where accuracy and aid are of utmost important for proper diagnosis and enhanced survival rate. In the following comprehensive study, we aim at developing a Computer Aided Diagnostic System for detecting the lung cancer in the patient based on the Computed Tomography scan along with the predicting the stage of lung cancer. The proposed model is based upon the two-dimensional Convolutional Neural Networks with accuracies of 99% and 98% respectively for both the stages-detection and prediction. In future we aim at developing this system for other types of cancers.

2016 International Conference on Communication and Signal Processing (ICCSP), 2016

Appropriate to fractional hardware and connectivity harms, picture dispensation on movable elegan... more Appropriate to fractional hardware and connectivity harms, picture dispensation on movable elegant cell phone is a fresh and pitiful ground by lots of plucky. Android supported cell headsets be currently enticing a center of some application. Here manuscript describes precise instance facade identification request replica used for chic receiver. Here initiate mold employ mixture skin hue-sentiment features discovery technique and interest point localization pro facet identical. This document be tilted in JAVA object oriented coding to entire Android chic receiver. Consequences can be revealed plus contrast among accessible free source systems designed for confirmation. This is aspiring to support valid point actions by lofty detection pace. Appliances series as of safety towards the citizens through immobilize revision.

2016 International Conference on Communication and Signal Processing (ICCSP), 2016

This paper proposed a new system for image based authentication, where the image is treaded as id... more This paper proposed a new system for image based authentication, where the image is treaded as identification of authenticated user. This system employs approach to store a unique id or password into image and helps to restrict unauthorized user access system. This proposed algorithm is help to eliminate the weakness of password authentication and bypass the risk generated from password authentication. This Authentication system helps to store product information over a network. Password provides security mechanism for authentication and protection services unwanted access to resource. In this paper we proposed a new QR code image password based system techniques that offer advantages over existing system.

IOSR Journal of Computer Engineering, 2013

Cataloging traffic keen on precise network applications is vital for application-aware network or... more Cataloging traffic keen on precise network applications is vital for application-aware network organization and it turn into more taxing because modern applications incomprehensible their network behaviors. Whereas port number-based classifiers work merely for a little renowned application and signaturebased classifiers are not significant to encrypted packet payloads, researchers are inclined to classify network traffic rooted in behaviors scrutinized in network applications. In this document, a session level Flood Cataloging (SLFC) approach is proposed to organize network Floods as a session, which encompasses of Floods in the equal discussion. SLFC initially classifies flood into the analogous applications by packet size distribution (PSD) and subsequently faction Floods as sessions by port locality. With PSD, each Flood is distorted into a set of points in a two-Dimension space and the remoteness among all Flood and the representatives of preselected applications are calculated. The Flood is predicted as the application having a least distance. Meanwhile, port locality is accustomed to cluster Floods as sessions since an application often uses successive port statistics surrounded by a session. If flood of a session are categorized into diverse applications, an arbitration algorithm is invoked to make the improvement.

Lung cancer holds the highest position in the list of reasons for deaths in the world. The limita... more Lung cancer holds the highest position in the list of reasons for deaths in the world. The limitations of most of the Computer Aided Design Systems is that they just predict the whether the given image is cancerous or non-cancerous. It is equally important to study how to detect the stage of the cancer from the extracted nodule. In this paper, we present a comparative analysis of the literature survey in terms of stage classification of lung cancer. The latest research trends are explored presenting their accuracies as well as limitations. Key Wordslung cancer classification, CAD system, benign or malignant, Neural networks, Deep Learning

International Journal of Pharmaceutical Research, Feb 2, 2021

Growing advancements in automation industry have paved a way for medicine domain in terms of CAD ... more Growing advancements in automation industry have paved a way for medicine domain in terms of CAD system as an aid for health practitioners. Lung cancer is one such disease where accuracy and aid are of utmost important for proper diagnosis and enhanced survival rate. In the following comprehensive study, we aim at developing a Computer Aided Diagnostic System for detecting the lung cancer in the patient based on the Computed Tomography scan along with the predicting the stage of lung cancer. The proposed model is based upon the two-dimensional Convolutional Neural Networks with accuracies of 99% and 98% respectively for both the stages-detection and prediction. In future we aim at developing this system for other types of cancers.

with the latest technical developments in healthcare, the emphasis has always been upon improving... more with the latest technical developments in healthcare, the emphasis has always been upon improving existing systems' speed and accuracy. Increasing survival rate of the patient from lung malignance is one of such challenge which interests researchers. lung cancer survival rate of patients depends upon the stage in which the cancer is detected. If detected in early (first) stage, there are more chances of the diseases to be cured and the survival chances of the patient are more than 50%. This requires the advanced analysis because the symptoms normally overlap with other lung diseases. CT scan images are widely used all over the world for this analysis. Image processing contributes significantly in analysis of the CT scan images. This paper sheds light on current literature strategies, with thorough studies of each phase. A comparative analysis has been presented. Final steps for the detection of lung cancer are then proposed based on the conclusions of the analysis.

The overlapping symptoms of lung cancer with other pulmonary diseases is one of the critical reas... more The overlapping symptoms of lung cancer with other pulmonary diseases is one of the critical reasons that makes it difficult to differentiate the lung nodule as cancerous or noncancerous. Computed Aided Design (CAD) systems are rigorously researched for enhancing the accuracy of the model to predict the nature of the detected nodule. The differentiation of a lung nodule into cancer or non-cancer, and nature as benign or malignant, are important aspects of analysis. The increasing use of technologies like deep learning and neural networks has proven to be the drivers of 12st century in all the domains of research. In the comprehensive study, we present a two-dimensional convolutional neural network for predicting the nodule. The accuracy of the presented model is 99% with the split ratio of the training into the ratio of 0.7:0.1:0.1.

Image segmentation is the crucial step in a Computer-aided diagnostic system. The recent advancem... more Image segmentation is the crucial step in a Computer-aided diagnostic system. The recent advancements in technological ways have explored all the possible ways of segmenting images, especially in lung cancer area to enhance accuracy with reduced time and complexity. In this study, we present a lung segmentation model on the basis of morphological functions which is used further for classification step. The accuracy with the proposed segmentation is achieved as 99% for binary classification of the lung image into benign and malignant. The method will be explored further to use it for other types of cancers.

Lung cancer holds the highest position in the list of reasons for deaths in the world. The limita... more Lung cancer holds the highest position in the list of reasons for deaths in the world. The limitations of most of the Computer Aided Design Systems is that they just predict the whether the given image is cancerous or non-cancerous. It is equally important to study how to detect the stage of the cancer from the extracted nodule. In this paper, we present a comparative analysis of the literature survey in terms of stage classification of lung cancer. The latest research trends are explored presenting their accuracies as well as limitations.

Growing advancements in automation industry have paved a way for medicine domain in terms of CAD ... more Growing advancements in automation industry have paved a way for medicine domain in terms of CAD system as an aid for health practitioners. Lung cancer is one such disease where accuracy and aid are of utmost important for proper diagnosis and enhanced survival rate. In the following comprehensive study, we aim at developing a Computer Aided Diagnostic System for detecting the lung cancer in the patient based on the Computed Tomography scan along with the predicting the stage of lung cancer. The proposed model is based upon the two-dimensional Convolutional Neural Networks with accuracies of 99% and 98% respectively for both the stages-detection and prediction. In future we aim at developing this system for other types of cancers.

2016 International Conference on Communication and Signal Processing (ICCSP), 2016

Appropriate to fractional hardware and connectivity harms, picture dispensation on movable elegan... more Appropriate to fractional hardware and connectivity harms, picture dispensation on movable elegant cell phone is a fresh and pitiful ground by lots of plucky. Android supported cell headsets be currently enticing a center of some application. Here manuscript describes precise instance facade identification request replica used for chic receiver. Here initiate mold employ mixture skin hue-sentiment features discovery technique and interest point localization pro facet identical. This document be tilted in JAVA object oriented coding to entire Android chic receiver. Consequences can be revealed plus contrast among accessible free source systems designed for confirmation. This is aspiring to support valid point actions by lofty detection pace. Appliances series as of safety towards the citizens through immobilize revision.

2016 International Conference on Communication and Signal Processing (ICCSP), 2016

This paper proposed a new system for image based authentication, where the image is treaded as id... more This paper proposed a new system for image based authentication, where the image is treaded as identification of authenticated user. This system employs approach to store a unique id or password into image and helps to restrict unauthorized user access system. This proposed algorithm is help to eliminate the weakness of password authentication and bypass the risk generated from password authentication. This Authentication system helps to store product information over a network. Password provides security mechanism for authentication and protection services unwanted access to resource. In this paper we proposed a new QR code image password based system techniques that offer advantages over existing system.

IOSR Journal of Computer Engineering, 2013

Cataloging traffic keen on precise network applications is vital for application-aware network or... more Cataloging traffic keen on precise network applications is vital for application-aware network organization and it turn into more taxing because modern applications incomprehensible their network behaviors. Whereas port number-based classifiers work merely for a little renowned application and signaturebased classifiers are not significant to encrypted packet payloads, researchers are inclined to classify network traffic rooted in behaviors scrutinized in network applications. In this document, a session level Flood Cataloging (SLFC) approach is proposed to organize network Floods as a session, which encompasses of Floods in the equal discussion. SLFC initially classifies flood into the analogous applications by packet size distribution (PSD) and subsequently faction Floods as sessions by port locality. With PSD, each Flood is distorted into a set of points in a two-Dimension space and the remoteness among all Flood and the representatives of preselected applications are calculated. The Flood is predicted as the application having a least distance. Meanwhile, port locality is accustomed to cluster Floods as sessions since an application often uses successive port statistics surrounded by a session. If flood of a session are categorized into diverse applications, an arbitration algorithm is invoked to make the improvement.

Lung cancer holds the highest position in the list of reasons for deaths in the world. The limita... more Lung cancer holds the highest position in the list of reasons for deaths in the world. The limitations of most of the Computer Aided Design Systems is that they just predict the whether the given image is cancerous or non-cancerous. It is equally important to study how to detect the stage of the cancer from the extracted nodule. In this paper, we present a comparative analysis of the literature survey in terms of stage classification of lung cancer. The latest research trends are explored presenting their accuracies as well as limitations. Key Wordslung cancer classification, CAD system, benign or malignant, Neural networks, Deep Learning