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Journal ArticleDOI

Ratsnake: a versatile image annotation tool with application to computer-aided diagnosis.

27 Jan 2014-The Scientific World Journal (Hindawi Publishing Corporation)-Vol. 2014, pp 286856-286856
TL;DR: Ratsnake is presented, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system.
Abstract: Image segmentation and annotation are key components of image-based medical computer-aided diagnosis (CAD) systems. In this paper we present Ratsnake, a publicly available generic image annotation tool providing annotation efficiency, semantic awareness, versatility, and extensibility, features that can be exploited to transform it into an effective CAD system. In order to demonstrate this unique capability, we present its novel application for the evaluation and quantification of salient objects and structures of interest in kidney biopsy images. Accurate annotation identifying and quantifying such structures in microscopy images can provide an estimation of pathogenesis in obstructive nephropathy, which is a rather common disease with severe implication in children and infants. However a tool for detecting and quantifying the disease is not yet available. A machine learning-based approach, which utilizes prior domain knowledge and textural image features, is considered for the generation of an image force field customizing the presented tool for automatic evaluation of kidney biopsy images. The experimental evaluation of the proposed application of Ratsnake demonstrates its efficiency and effectiveness and promises its wide applicability across a variety of medical imaging domains.

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Citations
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Book ChapterDOI
01 Jan 2005
TL;DR: The goal is to help developers find the most suitable language for their representation needs in the Semantic Web, which has a need for languages to represent the semantic information that this Web requires.
Abstract: being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web—known as the Semantic Web—which has been defined as “the conceptual structuring of the Web in an explicit machine-readable way.”1 This definition does not differ too much from the one used for defining an ontology: “An ontology is an explicit, machinereadable specification of a shared conceptualization.”2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires—solving the heterogeneous data exchange in this heterogeneous environment. Here, we don’t decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs.

212 citations

Journal ArticleDOI
TL;DR: An in-depth critical analysis is presented that aims to inspire and align the agendas of the two scientific groups in the field of small bowel diseases.
Abstract: Video capsule endoscopy (VCE) has revolutionized the diagnostic work-up in the field of small bowel diseases. Furthermore, VCE has the potential to become the leading screening technique for the entire gastrointestinal tract. Computational methods that can be implemented in software can enhance the diagnostic yield of VCE both in terms of efficiency and diagnostic accuracy. Since the appearance of the first capsule endoscope in clinical practice in 2001, information technology (IT) research groups have proposed a variety of such methods, including algorithms for detecting haemorrhage and lesions, reducing the reviewing time, localizing the capsule or lesion, assessing intestinal motility, enhancing the video quality and managing the data. Even though research is prolific (as measured by publication activity), the progress made during the past 5 years can only be considered as marginal with respect to clinically significant outcomes. One thing is clear-parallel pathways of medical and IT scientists exist, each publishing in their own area, but where do these research pathways meet? Could the proposed IT plans have any clinical effect and do clinicians really understand the limitations of VCE software? In this Review, we present an in-depth critical analysis that aims to inspire and align the agendas of the two scientific groups.

187 citations

Journal ArticleDOI
TL;DR: A simple, yet effective approach allowing automatic detection of all types of abnormalities in capsule endoscopy is presented, which outperforms previous state-of-the-art approaches and is robust in the presence of luminal contents and is capable of detecting even very small lesions.

102 citations


Cites background or methods from "Ratsnake: a versatile image annotat..."

  • ...1B), publicly available software for image annotation.(5) Annotated images were exported as masks, ie, black-and-white frames in which any pathology is depicted as white area on a black background (Fig....

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  • ...However, it has a high complexity and does not directly address the issue of automated lesion detection.(5) A methodology designed for the detection of a wide variety of lesions, regardless of their type or size, should be able to overcome such limitations....

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Journal ArticleDOI
TL;DR: MLA can perform as well as human readers in the measurement of SB angioectasias in white light (WL) and Automated lesion measurement is therefore feasible.
Abstract: Background and aims Capsule endoscopy (CE) has revolutionized small-bowel (SB) investigation Computational methods can enhance diagnostic yield (DY); however, incorporating machine learning algorithms (MLAs) into CE reading is difficult as large amounts of image annotations are required for training Current databases lack graphic annotations of pathologies and cannot be used A novel database, KID, aims to provide a reference for research and development of medical decision support systems (MDSS) for CE Methods Open-source software was used for the KID database Clinicians contribute anonymized, annotated CE images and videos Graphic annotations are supported by an open-access annotation tool (Ratsnake) We detail an experiment based on the KID database, examining differences in SB lesion measurement between human readers and a MLA The Jaccard Index (JI) was used to evaluate similarity between annotations by the MLA and human readers Results The MLA performed best in measuring lymphangiectasias with a JI of 81 ± 6 % The other lesion types were: angioectasias (JI 64 ± 11 %), aphthae (JI 64 ± 8 %), chylous cysts (JI 70 ± 14 %), polypoid lesions (JI 75 ± 21 %), and ulcers (JI 56 ± 9 %) Conclusion MLA can perform as well as human readers in the measurement of SB angioectasias in white light (WL) Automated lesion measurement is therefore feasible KID is currently the only open-source CE database developed specifically to aid development of MDSS Our experiment demonstrates this potential

99 citations


Additional excerpts

  • ...Semantic and graphic annotations are supported by an open access, platform-independent annotation tool (Ratsnake) [8]....

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Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors explored the dynamic mechanical properties and crack propagation law of rock under high strain rate impact loading, an experimental investigation with 12 sets of Brazilian disk (BD) rock specimens under Split Hopkinson Pressure Bar (SHPB) loading was undertaken.

87 citations

References
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Journal ArticleDOI
TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Abstract: Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

35,225 citations

Journal ArticleDOI
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Abstract: A snake is an energy-minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines and edges. Snakes are active contour models: they lock onto nearby edges, localizing them accurately. Scale-space continuation can be used to enlarge the capture region surrounding a feature. Snakes provide a unified account of a number of visual problems, including detection of edges, lines, and subjective contours; motion tracking; and stereo matching. We have used snakes successfully for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest.

18,095 citations


"Ratsnake: a versatile image annotat..." refers background or methods in this paper

  • ...Representative examples include the gradient vector field [33] and the boundary vector field models [34], which efficiently cope with the well-known limitations of the original snake model [3]....

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  • ...The efficiency of this tool relies on a simple graphical user interface (GUI), featuring complementary graphic annotation protocols and a properly modified snake model [3], which in its original form enables semiautomatic image segmentation....

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Proceedings Article
Ron Kohavi1
20 Aug 1995
TL;DR: The results indicate that for real-word datasets similar to the authors', the best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.
Abstract: We review accuracy estimation methods and compare the two most common methods crossvalidation and bootstrap. Recent experimental results on artificial data and theoretical re cults in restricted settings have shown that for selecting a good classifier from a set of classifiers (model selection), ten-fold cross-validation may be better than the more expensive leaveone-out cross-validation. We report on a largescale experiment--over half a million runs of C4.5 and a Naive-Bayes algorithm--to estimate the effects of different parameters on these algrithms on real-world datasets. For crossvalidation we vary the number of folds and whether the folds are stratified or not, for bootstrap, we vary the number of bootstrap samples. Our results indicate that for real-word datasets similar to ours, The best method to use for model selection is ten fold stratified cross validation even if computation power allows using more folds.

11,185 citations


"Ratsnake: a versatile image annotat..." refers methods in this paper

  • ...Tenfold cross-validation has been adopted as a widely accepted method to assess classification accuracy [45]; that is, the dataset was randomly split into 10 mutually exclusive subsets, leaving out one set for testing and using the other nine as training, exhaustively, until all of them serve as testing sets....

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Proceedings ArticleDOI
25 Jun 2006
TL;DR: It is shown that a deep connection exists between ROC space and PR space, such that a curve dominates in R OC space if and only if it dominates in PR space.
Abstract: Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning. However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm's performance. We show that a deep connection exists between ROC space and PR space, such that a curve dominates in ROC space if and only if it dominates in PR space. A corollary is the notion of an achievable PR curve, which has properties much like the convex hull in ROC space; we show an efficient algorithm for computing this curve. Finally, we also note differences in the two types of curves are significant for algorithm design. For example, in PR space it is incorrect to linearly interpolate between points. Furthermore, algorithms that optimize the area under the ROC curve are not guaranteed to optimize the area under the PR curve.

5,063 citations


"Ratsnake: a versatile image annotat..." refers background in this paper

  • ...The results obtained per class are presented in Table 2, where class precision and recall refer to the capability of the classifier to identify relevant image samples and to correctly label them, respectively [46]....

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Journal ArticleDOI
TL;DR: Standard alphabetical procedures for organizing lexical information put together words that are spelled alike and scatter words with similar or related meanings haphazardly through the list.
Abstract: Standard alphabetical procedures for organizing lexical information put together words that are spelled alike and scatter words with similar or related meanings haphazardly through the list. Unfortunately, there is no obvious alternative, no other simple way for lexicographers to keep track of what has been done or for readers to find the word they are looking for. But a frequent objection to this solution is that finding things on an alphabetical list can be tedious and time-consuming. Many people who would like to refer to a dictionary decide not to bother with it because finding the information would interrupt their work and break their train of thought.

5,038 citations


"Ratsnake: a versatile image annotat..." refers methods in this paper

  • ...The semantic annotations of LabelMe are based on free text or a lexical database called WordNet [29]....

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