Harish Srinivasan

• RMK Engineering College

About 70% of newly diagnosed cases of bladder cancer are low-stage, low-grade, non muscle-invasive. Standard treatment is transurethral resection. About 60% of the tumours will recur, however, and in part progress to become invasive. Therefore, surveillance cystoscopy is performed after resection. However, in the USA and Europe alone, about 54,000...

Effective prediction of diagnosis and prognosis in cancer is an important step for selection of a suitable treatment regimen. In this dissertation, the importance of using antibody microarray for effective diagnosis and prognosis of cancer was studied using bladder and gastric cancers. In the first part of study, establishment of a protein signatu...

In this study, plasma samples from a multicentric case-control study on lymphoma were analyzed for the identification of proteins useful for diagnosis. The protein content in the plasma of 100 patients suffering from the three most common B-cell lymphomas and 100 control samples was studied with antibody microarrays composed of 810 antibodies that...

Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Express...

Range of WG score. (PPT)

List of genes selected for expression analysis by RT-qPCR. (DOCX)

Case bias analysis in the present data set. (DOCX)

List of differentially regulated genes between high risk and low risk patients derived from TCGA data set. (DOCX)

Details of primers used for RT-qPCR. (DOCX)

Univariate and multivariate analysis of WG score with other signatures. (DOCX)

Genes selected from full data during cross validation. (DOCX)

Transcript levels of 14 genes in four glioma subtypes. (DOCX)

Identification and validation of fourteen gene signature. (PPT)

Comparison of gene expression in present data set and TCGA data set. (DOCX)

Survival based on risk stratification by SWG score. (DOCX)

The expression pattern of genes in low risk and high risk groups in the TCGA data set. (DOCX)

Given an ambiguous person name as input, a cross-document person name disambiguation system clus-ters documents so that each cluster contains all and only those documents referring to the same person. In this paper we present our approach to this task. We introduce novel features based on topic models and also document-level entity profiles—sets of...

During the last few years many document recognition methods have been developed to determine whether a handwriting specimen can be attributed to a known writer. However, in practice, the work-flow of the document examiner continues to be manual-intensive. Before a systematic or computational, approach can be developed, an articulation of the steps...

Forensic individualization is the task of associating observed evidence with a specific source. The likelihood ratio (LR) is a quantitative measure that expresses the degree of uncertainty in individualization, where the numerator represents the likelihood that the evidence corresponds to the known and the denominator the likelihood that it does no...

Insulin-like growth factor (IGF)-binding protein (IGFBP) isoforms have been implicated in the pathogenesis of human neoplasms including glioma. In view of this, we evaluated the expression of IGFBP isoforms (IGFBP-2, -3, and -5) during malignant progression of astrocytoma and their prognostic significance in glioblastoma. The expression of IGFBP is...

The aim of this study is to identify serum biomarkers with classification and prognosis utility for astrocytoma, in particular glioblastoma (GBM). Our previous glioma microarray database was mined to identify genes that encode secreted or membrane-localized proteins. Subsequent analysis was done using significant analysis of microarrays, followed b...

In searching a large repository of scanned documents, a task of interest is that of retrieving documents from a database using a signature image as a query. This chapter presents a signature retrieval strategy using document indexing and retrieval. Indexing is done using (i) a model based on Conditional Random Fields (CRF) to label extracted segmen...

The fully Bayesian approach has been shown to be powerful in machine learning. This paper describes signature verification using a non-parametric Bayesian approach. Given sample(s) of Genuine signatures of an individual, the task of signature verification is a problem of classifying a questioned signature as Genuine or Forgery. The verification p...

As handwriting is influenced by physiology, training, and other behavioral factors, a study of the handwriting of twins can shed light on the individuality of handwriting. This paper describes the methodology and results of such a study where handwriting samples of twins were compared by an automatic handwriting verification system. The results com...

Searching handwritten documents is a relatively unexplored frontier for documents in any language. Traditional approaches use either image-based or text-based techniques. This paper describes a framework for versatile search where the query can be either text or image, and the retrieval method fuses text and image retrieval methods. A UNICODE and a...

Reading comprehension is largely tested in schools using handwritten responses. The paper describes computational methods of scoring such responses using handwriting recognition and automatic essay scoring technologies. The goal is to assign to each handwritten response a score which is comparable to that of a human scorer even though machine handw...

Line segmentation is the first and the most critical pre-processing step for a document recognition/analysis task. Complex handwritten documents with lines running into each other impose a great challenge for the line segmen- tation problem due to the absence of online stroke information. This paper describes a method to disentangle lines running i...

A study of the discriminability of fingerprints of twins is presented. The fingerprint data used is of high quality and quan-tity because of a predominantly young subject population of 298 pairs of twins whose tenprints were captured using a livescan device. Discriminability using level 1 and level 2 features is independently reported. The level 1...

Signature verification is a common task in forensic document analysis. It's aim is to determine whether a questioned signature matches known signature samples. From the viewpoint of automating the task it can be viewed as one that involves machine learning from a population of signatures. There are two types of learning tasks to be accomplished: pe...

The paper describes a lexicon driven approach for word recognition on handwritten documents using conditional random fields (CRFs). CRFs are discriminative models and do not make any assumptions about the underlying data and hence are known to be superior to hidden Markov models (HMMs) for sequence labeling problems. For word recognition, the docum...

Document examiners use a variety of features to analyze a given handwritten document for writer verification. The challenge in the automatic classification of a pair of documents to belong to the same or different writer, are both (i)The task of proper selection and extraction of features from the handwritten document and (ii)The use of a proper mo...

The problem of writer verification is to make a decision of whether or not two handwritten documents are written by the same person. Providing a strength of evidence for any such decision is an integral part of the writer verification problem. The strength of evidence should incorporate (i) The amount of information compared in each of the two docu...

Generative models of pattern individuality attempt to represent the distribution of observed quantitative features, e.g., by learning parameters from a database, and then use such distributions to determine the probability of two random patterns being the same. Considering fingerprint patterns, Gaussian distributions have been previously used for m...

The biometric verification task is one of determining whether an input consisting of measurements from an unknown individual matches the corresponding measurements of a known individual. This chapter describes a statistical learning methodology for determining whether a pair of biometric samples belong to the same individual. The methodology involv...

Matching of partial fingerprints has important applications in both biometrics and forensics. It is well-known that the accuracy of minutiae-based matching algorithms dramatically decrease as the number of available minutiae decreases. When singular structures such as core and delta are unavailable, general ridges can be utilized. Some existing hig...

Signatures and handwriting have long played a role in day- to-day business transactions and in forensics, e.g., to authenticate docu- ments, as evidence to establish crime or innocence, etc. The individuality of handwriting and signatures is the basis for their relevance to authenti- cation and forensics. This very individuality makes them also pot...

The paper describes the use of Conditional Random Fields(CRF) utilizing contextual information in automati-cally labeling extracted segments of scanned documents as Machine-print, Handwriting and Noise. The result of such a labeling can serve as an indexing step for a context-based image retrieval system or a bio-metric signature verification syste...

A new technique to segment a handwritten document into distinct lines of text is presented. Line segmentation is the first and the most critical pre-processing step for a document recognition/analysis task. The proposed algorithm starts, by obtaining an initial set of candidate lines from the piece-wise projection profile of the document. The lines...

Automating the task of scoring short handwritten student essays is considered. The goal is to as- sign scores which are comparable to those of hu- man scorers by coupling two AI technologies: op- tical handwriting recognition and automated essay scoring. The test-bed is that of essays written by children in reading comprehension tests. The pro- ces...

The problem of writer verification is to make a decision of whether or not two handwritten documents are written by the same person. Providing a strength of evidence for any such decision is an integral part of the writer verification problem. The strength of evidence should incorporate (i) The amount of information compared in each of the two docu...

The paper describes a lexicon driven approach for word recognition on handwritten documents using conditional random fields (CRFs). CRFs are discriminative models and do not make any assumptions about the underlying data and hence are known to be superior to hidden Markov models (HMMs) for sequence labeling problems. For word recognition, the docum...

Over a hundred years, several attempts have been made to quantitatively establish the degree of individuality of fingerprints. Measurements have been made using models based on grids, ridges, fixed probabilities, relative measurements and generative distributions. This paper is a survey and assessment of various fingerprint individuality models pro...

Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is gener-ating candida...

The flngerprint veriflcation task answers the question of whether or not two flngerprints belongs to the same flnger. The paper focuses on the classiflcation aspect of flngerprint veriflcation. Classiflcation is the third and flnal step after after the two earlier steps of feature extraction, where a known set of features (minutiae points) have bee...

Handwritten essays are widely used in educational assessments, particularly in classroom instruction. This paper concerns the design of an automated system for performing the task of taking as input scanned images of handwritten student essays in reading com- prehension tests and to produce as output scores for the answers which are analogous to th...

The design and performance of a system for spotting handwritten Arabic words in scanned document images is presented. Three main components of the system are a word segmenter, a shape based matcher for words and a search interface. The user types in a query in English within a search window, the system finds the equivalent Arabic word, e.g., by dic...

In searching a repository of business documents, a task of interest is that of using a query signature image to retrieve from a database, other signatures matching the query. The signature retrieval task involves a two-step process of extracting all the signatures from the documents and then performing a match on these signatures. This paper presen...

Signature verification is a common task in forensic document analysis. It is one of determining whether a questioned signature matches known signature samples. From the viewpoint of automating the task it can be viewed as one that involves machine learning from a population of signatures. There are two types of learning to be accomplished. In the f...

A system for spotting words in scanned docu-ment images in three scripts, Devanagari, Ara-bic and Latin is described. Three main com-ponents of the system are a word segmenter, a shape based matcher for words and a search in-terface. The user gives a query which can be ei-ther a word image or text. The candidate words that are searched in the docum...

New machine learning strategies are proposed for person identification which can be used in several biometric modalities such as friction ridges, handwriting, signatures and speech. The biometric or forensic performance task answers the question of whether or not a sample belongs to a known person. Two different learning paradigms are discussed: pe...

Automatic signature verification of scanned documents are presented here. The strat-egy used for verification is applicable in scenarios where there are multiple knowns(genuine signature samples) from a writer. First the learning process invovles learning the variation and similarities from the known genuine samples from the given writer and then c...

Search aspects of a system for analyzing handwritten documents are described. Documents are indexed using global image features, e.g., stroke width, slant as well as local features that describe the shapes of words and characters. Image indexing is done automatically using page analysis, page segmentation, line separation, word segmentation and rec...

This paper is about retrieving the closest matches from a set of scanned handwritten documents based on a query that is a document image. System indexing and retrieval is based on writer characteristics, textual content as well as document meta data such as writer profile. Documents are indexed using global image features, e.g., stroke width, slant...

An algorithm and a system for searching hand-written Arabic documents to locate key words is pre-sented. Three main components of the system are a word segmenter, a shape based matcher for words and a search interface. The user types in a query in English within a search window, the system finds the equivalent Arabic word, e.g., by dictionary look-...

A new approach to off-line signature verication using non parametric Bayesian approach is discussed. Given sample(s) of Genuine signatures of an individual, the task of signature verication is a problem of classifying a questioned(test) signature as Genuine or Forgery(skilled). The verication problem is a two step approach - (i)Enrollment: Genuine...

An algorithm to extract textual lines from document images where there is poor line structure, e.g., line skew and line interference, is presented. Simple line structures are handled with projection-profiles. Components that straddle multiple lines are assigned to lines by using statistical models of object pixels in lines. Overlapping components f...