PCA based clustering for brain tumor segmentation of T1w MRI images

This paper presents the state-of-the-art technical reviews and analysis of recent copy-move forgery detection (CMFD) techniques. A new CMFD process pipeline was introduced. In addition, the techniques used in each stage of the CMFD pipeline are summarized and classified into small categories. Furthermore, the tables of comparison are provided as a quick reference. This technical review paper is expected to help provide useful insights and updated information regarding recent advancements in CMFD to researchers in the field.

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Copy-Move Forgery Detection: A State-of-the-Art Technical Review and Analysis

Computed tomography (CT) scans are indispensable in modern medicine; however, the spectacular rise in global use coupled with relatively high doses of ionizing radiation per examination have raised radiation protection concerns. Children are of particular concern because they are more sensitive to radiation-induced cancer compared with adults and have a long lifespan to express harmful effects which may offset clinical benefits of performing a scan. This paper describes the design and methodology of a nationwide study, the Dutch Pediatric CT Study, regarding risk of leukemia and brain tumors in children after radiation exposure from CT scans. It is a retrospective record-linkage cohort study with an expected number of 100,000 children who received at least one electronically archived CT scan covering the calendar period since the introduction of digital archiving until 2012. Information on all archived CT scans of these children will be obtained, including date of examination, scanned body part and radiologist's report, as well as the machine settings required for organ dose estimation. We will obtain cancer incidence by record linkage with external databases. In this article, we describe several approaches to the collection of data on archived CT scans, the estimation of radiation doses and the assessment of confounding. The proposed approaches provide useful strategies for data collection and confounder assessment for general retrospective record-linkage studies, particular those using hospital databases on radiological procedures for the assessment of exposure to ionizing or non-ionizing radiation.

Leukemia and brain tumors among children after radiation exposure from CT scans : design and methodological opportunities of the Dutch Pediatric CT Study

With the deployments of Electronic Health Records (EHR), interoperability testing in healthcare is becoming crucial. EHR enables access to prior diagnostic information in order to assist in health decisions. It is a virtual system that results from the cooperation of several heterogeneous distributed systems. Interoperability between peers is therefore essential. Achieving interoperability requires various types of testing. Implementations need to be tested using software that simulates communication partners, and that provides test data and test plans. In this paper we describe a software that is used to test systems that are involved in sharing medical images within the EHR. Our software is used as part of the Integrating the Healthcare Enterprise (IHE) testing process to test the Cross Enterprise Document Sharing for imaging (XDS-I) integration profile. We describe its architecture and functionalities; we also expose the challenges encountered and discuss the elected design solutions. EHR is being deployed in several countries. The EHR infrastructure will be continuously evolving to embrace advances in the information technology domain. Our software is built on a web framework to allow for an easy evolution with web technology. The testing software is publicly available; it can be used by system implementers to test their implementations. It can also be used by site integrators to verify and test the interoperability of systems, or by developers to understand specifications ambiguities, or to resolve implementations difficulties.

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IHE cross-enterprise document sharing for imaging: interoperability testing software.

Research in burns has been a continuing demand over the past few decades, and important advancements are still needed to facilitate more effective patient stabilization and reduce mortality rate. Burn wound assessment, which is an important task for surgical management, largely depends on the accuracy of burn area and burn depth estimates. Automated quantification of these burn parameters plays an essential role for reducing these estimate errors conventionally carried out by clinicians. The task for automated burn area calculation is known as image segmentation. In this paper, a new segmentation method for burn wound images is proposed. The proposed methods utilizes a method of tensor decomposition of colour images, based on which effective texture features can be extracted for classification. Experimental results showed that the proposed method outperforms other methods not only in terms of segmentation accuracy but also computational speed.

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Tensor Decomposition for Colour Image Segmentation of Burn Wounds

Physician use medical images to find abnormalities in human bodies and to locate the discontinuities. In transmission process sometimes medical images are corrupted due to external noise. Therefore need to improve the image quality, put down the computational complexity and signal to noise ratio. There is need of segmentation to improve performance analysis and image quality. Segmentation method is use to identify important regions in medical images, it is a unique technique for partitioning image into meaningful sub regions or object with same attribute. Proposed method state Principle component analysis and k-means clustering method for segmentation of medical images and extracts meaningful part from medical image in efficient manner. K-means Clustering is the process of extracting meaningful part from image. Adding Principle Component Analysis for feature extraction and formation of precise number of cluster to increase the accuracy. To develop a system which will perform segmentation of MRI images to locate disorder in better way.

A novel approach for medical image segmentation using PCA and K-means clustering

MapReduce has been widely applied in various fields of data and compute intensive applications and also it is important programming model for cloud computing. Hadoop is an open-source implementation of MapReduce which operates on terabytes of data using commodity hardware. We have applied this Hadoop MapReduce programming model for analyzing web log files so that we could get hit count of specific web application. This system uses Hadoop file system to store log file and results are evaluated using Map and Reduce function. Experimental results show hit count for each field in log file. Also due to MapReduce runtime parallelization response time is reduced.

Analyzing web application log files to find hit count through the utilization of Hadoop MapReduce in cloud computing environment

Handwriting analysis is the scientific method or way of determining or understanding or predicting the personality or behavior of a writer. Graphology or graph analysis is the scientific name of handwriting analysis. Handwriting often called as brain writing or mind writing, since it is a system of studying the frozen graphic structures which have been generated in the brain and placed on paper in a printed or cursive style. Many things can be revealed from handwriting such as anger, morality, fears, past experience, hidden talents, mental problems. Handwriting is different from person to person. People are facing various psychological problems. Teenagers also face so many mental problems. Criminals can be detected by using handwriting analysis. Counselor and mentor can also use this tool for giving advice to clients. Proposed work contains three main steps: image preprocessing, identification of handwriting features, and mapping of identified features with personality traits. Image pre-processing is the technique in which the handwriting sample is translated into a format which can be easily and efficiently processed in further steps. These steps involve noise removal, grayscale, thresholding, and image morphology. In feature identification, there is an extraction of handwriting features. Three features of handwriting are extracted that are left margin, right margin, and word spacing. Lastly, extracted features are mapped with personality using the rule-based technique. The personality of a writer with respect to three handwriting features is displayed. The proposed system can predict 90% accurate personality of the person.

A Model for Determining Personality by Analyzing Off-line Handwriting

With use of advanced image processing software's and tools, it becomes very easy to perform the tampering on original digital images with different intensions. Such kind of image tampering or manipulation is collectively called as image forgery. The main two types are 1) copy-move forgery and 2) image splicing forgery of image forgery. Copy-move tampering is most generally used by attackers in which object of another image is copy and paste in original image in nearly matching areas. Hence to identify such image threats, it is required to automatic computer vision based method which can classify whether input digital image is original or tampered. The image processing based methods are mainly three important phases like as image pre-processing, image features extraction and detection of forged area on image using features extracted. For copy-move forgery detection there are many methods introduced from last 15 years. This all methods are categorized in two main types is active and passive forgery detection methods. This paper scope is limited to study on passive forgery detection methods. In this paper, aim is to present the study on different old methods of image forgery detection using different approaches like DWT (Discrete Wavelet Transform), SIFT, LBP (Local Binary Pattern) etc. The outcome of this paper is to find the current research challenges based on study of different methods of image forgery detection through the comparative study of all recent methods studied.

Study and analysis of copy-move & splicing image forgery detection techniques

There has been a wide development in the zone of advanced picture usage. One of the fundamental problems in this present reality is to judge the genuineness of a particular picture. These days it is anything but difficult to alter and manufacture computerized picture with the progression of the capable advanced picture handling programming and simple accessibility of the apparatuses. The most widely recognized type of picture control systems is the district duplication additionally called as duplicate move falsification where a segment of the picture is replicated and glue to another part in the same advanced picture. To examine such legal investigation, different procedures and technique have been created in the past writing. In this paper will utilize productive calculations in light of Local Binary Pattern (LBP) with discrete wavelet transform (DWT) and principle component analysis (PCA). Firstly, change the picture from RGB to YCbCr by applying Pre-processing. Secondly, Discrete Wavelet Transform is applied above the image for compression. Guess sub-picture contains low recurrence parts having most extreme data. LL sub-picture is separated in covering squares. Thirdly Local Binary Pattern is performed. Fourthly principle component analysis utilized to match between chunks as feature matching. The latest step is support vector machine (SVM) classify to choice of which slice is the fake.

Trupti Baraskar

Papers

A novel approach for medical image segmentation using PCA and K-means clustering

Analyzing web application log files to find hit count through the utilization of Hadoop MapReduce in cloud computing environment

A Model for Determining Personality by Analyzing Off-line Handwriting

Study and analysis of copy-move & splicing image forgery detection techniques

Detection of Copy-Move Image Forgery Using Local Binary Pattern with Discrete Wavelet Transform and Principle Component Analysis