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| Author | Patricia Suarez; Angel Sappa; Boris X. Vintimilla | ||||
| Title | Deep learning-based vegetation index estimation | Type | Book Chapter | ||
| Year | 2021 | Publication | Generative Adversarial Networks for Image-to-Image Translation | Abbreviated Journal | |
| Volume | Issue | Pages  |
205-234 | ||
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| Abstract | Chapter 9 | ||||
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| Publisher | Elsevier | Place of Publication | Editor | A.Solanki; A.Nayyar; M.Naved | |
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| Area | Expedition | Conference | |||
| Notes | MSIAU; 600.122 | Approved | no | ||
| Call Number | Admin @ si @ SSV2021a | Serial | 3578 | ||
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| Author | Lluis Gomez; Dimosthenis Karatzas | ||||
| Title | Object Proposals for Text Extraction in the Wild | Type | Conference Article | ||
| Year | 2015 | Publication | 13th International Conference on Document Analysis and Recognition ICDAR2015 | Abbreviated Journal | |
| Volume | Issue | Pages |
206 - 210 | ||
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| Abstract | Object Proposals is a recent computer vision technique receiving increasing interest from the research community. Its main objective is to generate a relatively small set of bounding box proposals that are most likely to contain objects of interest. The use of Object Proposals techniques in the scene text understanding field is innovative. Motivated by the success of powerful while expensive techniques to recognize words in a holistic way, Object Proposals techniques emerge as an alternative to the traditional text detectors. In this paper we study to what extent the existing generic Object Proposals methods may be useful for scene text understanding. Also, we propose a new Object Proposals algorithm that is specifically designed for text and compare it with other generic methods in the state of the art. Experiments show that our proposal is superior in its ability of producing good quality word proposals in an efficient way. The source code of our method is made publicly available | ||||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 600.077; 600.084; 601.197 | Approved | no | ||
| Call Number | Admin @ si @ GoK2015 | Serial | 2691 | ||
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| Author | David Lloret; Joan Serrat; Antonio Lopez; A. Soler; Juan J. Villanueva | ||||
| Title | Retinal image registration using creases as anatomical landmarks. | Type | Conference Article | ||
| Year | 2000 | Publication | 15 th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | 3 | Issue | Pages |
207-2010 | |
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| Abstract | Retinal images are routinely used in ophthalmology to study the optical nerve head and the retina. To assess objectively the evolution of an illness, images taken at different times must be registered. Most methods so far have been designed specifically for a single image modality, like temporal series or stereo pairs of angiographies, fluorescein angiographies or scanning laser ophthalmoscope (SLO) images, which makes them prone to fail when conditions vary. In contrast, the method we propose has shown to be accurate and reliable on all the former modalities. It has been adapted from the 3D registration of CT and MR image to 2D. Relevant features (also known as landmarks) are extracted by means of a robust creaseness operator, and resulting images are iteratively transformed until a maximum in their correlation is achieved. Our method has succeeded in more than 100 pairs tried so far, in all cases including also the scaling as a parameter to be optimized | ||||
| Address | Barcelona. | ||||
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| Language | Summary Language | Original Title | |||
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| Area | Expedition | Conference | ICPR | ||
| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ LSL2000 c | Serial | 233 | ||
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| Author | Bogdan Raducanu; D. Gatica-Perez | ||||
| Title | Inferring competitive role patterns in reality TV show through nonverbal analysis | Type | Journal Article | ||
| Year | 2012 | Publication | Multimedia Tools and Applications | Abbreviated Journal | MTAP |
| Volume | 56 | Issue | 1 | Pages |
207-226 |
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| Abstract | This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority. | ||||
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| Publisher | Elsevier | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1380-7501 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaG2012 | Serial | 1360 | ||
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| Author | P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes | ||||
| Title | A Novel Learning-free Word Spotting Approach Based on Graph Representation | Type | Conference Article | ||
| Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
| Volume | Issue | Pages |
207-211 | ||
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| Abstract | Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods. | ||||
| Address | Tours; France; April 2014 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ WEG2014b | Serial | 2517 | ||
| Permanent link to this record | |||||
| Author | Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta | ||||
| Title | The ICDAR/GREC 2013 Music Scores Competition: Staff Removal | Type | Book Chapter | ||
| Year | 2014 | Publication | Graphics Recognition. Current Trends and Challenges | Abbreviated Journal | |
| Volume | 8746 | Issue | Pages |
207-220 | |
| Keywords | Competition; Graphics recognition; Music scores; Writer identification; Staff removal | ||||
| Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations. | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | B.Lamiroy; J.-M. Ogier | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-662-44853-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes | DAG; 600.077; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ FKV2014 | Serial | 2581 | ||
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| Author | Bhaskar Chakraborty; Marco Pedersoli; Jordi Gonzalez | ||||
| Title | View-Invariant Human Action Detection using Component-Wise HMM of Body Parts | Type | Book Chapter | ||
| Year | 2008 | Publication | Articulated Motion and Deformable Objects, 5th International Conference | Abbreviated Journal | |
| Volume | 5098 | Issue | Pages |
208–217 | |
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| Address | Port d'Andratx (Mallorca) | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | AMDO | ||
| Notes | ISE | Approved | no | ||
| Call Number | ISE @ ise @ CPG2008 | Serial | 975 | ||
| Permanent link to this record | |||||
| Author | Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu | ||||
| Title | Switching off brightness induction through induction-reversed images | Type | Abstract | ||
| Year | 2012 | Publication | Perception | Abbreviated Journal | PER |
| Volume | 41 | Issue | Pages |
208 | |
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| Abstract | Brightness induction is the modulation of the perceived intensity of an
area by the luminance of surrounding areas. Although V1 is traditionally regarded as an area mostly responsive to retinal information, neurophysiological evidence suggests that it may explicitly represent brightness information. In this work, we investigate possible neural mechanisms underlying brightness induction. To this end, we consider the model by Z Li (1999 Computation and Neural Systems10187-212) which is constrained by neurophysiological data and focuses on the part of V1 responsible for contextual influences. This model, which has proven to account for phenomena such as contour detection and preattentive segmentation, shares with brightness induction the relevant effect of contextual influences. Importantly, the input to our network model derives from a complete multiscale and multiorientation wavelet decomposition, which makes it possible to recover an image reflecting the perceived luminance and successfully accounts for well known psychophysical effects for both static and dynamic contexts. By further considering inverse problem techniques we define induction-reversed images: given a target image, we build an image whose perceived luminance matches the actual luminance of the original stimulus, thus effectively canceling out brightness induction effects. We suggest that induction-reversed images may help remove undesired perceptual effects and can find potential applications in fields such as radiological image interpretation |
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| Area | Expedition | Conference | |||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ PDO2012a | Serial | 2180 | ||
| Permanent link to this record | |||||
| Author | Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta | ||||
| Title | Large-scale Graph Indexing using Binary Embeddings of Node Contexts | Type | Conference Article | ||
| Year | 2015 | Publication | 10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition | Abbreviated Journal | |
| Volume | 9069 | Issue | Pages |
208-217 | |
| Keywords | Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding | ||||
| Abstract | Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents. | ||||
| Address | Beijing; China; May 2015 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer International Publishing | Place of Publication | Editor | C.-L.Liu; B.Luo; W.G.Kropatsch; J.Cheng | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-319-18223-0 | Medium | |
| Area | Expedition | Conference | GbRPR | ||
| Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
| Call Number | Admin @ si @ RLF2015a | Serial | 2618 | ||
| Permanent link to this record | |||||
| Author | Mikkel Thogersen; Sergio Escalera; Jordi Gonzalez; Thomas B. Moeslund | ||||
| Title | Segmentation of RGB-D Indoor scenes by Stacking Random Forests and Conditional Random Fields | Type | Journal Article | ||
| Year | 2016 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 80 | Issue | Pages |
208–215 | |
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| Abstract | This paper proposes a technique for RGB-D scene segmentation using Multi-class
Multi-scale Stacked Sequential Learning (MMSSL) paradigm. Following recent trends in state-of-the-art, a base classifier uses an initial SLIC segmentation to obtain superpixels which provide a diminution of data while retaining object boundaries. A series of color and depth features are extracted from the superpixels, and are used in a Conditional Random Field (CRF) to predict superpixel labels. Furthermore, a Random Forest (RF) classifier using random offset features is also used as an input to the CRF, acting as an initial prediction. As a stacked classifier, another Random Forest is used acting on a spatial multi-scale decomposition of the CRF confidence map to correct the erroneous labels assigned by the previous classifier. The model is tested on the popular NYU-v2 dataset. The approach shows that simple multi-modal features with the power of the MMSSL paradigm can achieve better performance than state of the art results on the same dataset. |
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| Notes | HuPBA; ISE;MILAB; 600.098; 600.119 | Approved | no | ||
| Call Number | Admin @ si @ TEG2016 | Serial | 2843 | ||
| Permanent link to this record | |||||
| Author | David Masip; Alexander Todorov; Jordi Vitria | ||||
| Title | The Role of Facial Regions in Evaluating Social Dime | Type | Conference Article | ||
| Year | 2012 | Publication | 12th European Conference on Computer Vision – Workshops and Demonstrations | Abbreviated Journal | |
| Volume | 7584 | Issue | II | Pages |
210-219 |
| Keywords | Workshops and Demonstrations | ||||
| Abstract | Facial trait judgments are an important information cue for people. Recent works in the Psychology field have stated the basis of face evaluation, defining a set of traits that we evaluate from faces (e.g. dominance, trustworthiness, aggressiveness, attractiveness, threatening or intelligence among others). We rapidly infer information from others faces, usually after a short period of time (< 1000ms) we perceive a certain degree of dominance or trustworthiness of another person from the face. Although these perceptions are not necessarily accurate, they influence many important social outcomes (such as the results of the elections or the court decisions). This topic has also attracted the attention of Computer Vision scientists, and recently a computational model to automatically predict trait evaluations from faces has been proposed. These systems try to mimic the human perception by means of applying machine learning classifiers to a set of labeled data. In this paper we perform an experimental study on the specific facial features that trigger the social inferences. Using previous results from the literature, we propose to use simple similarity maps to evaluate which regions of the face influence the most the trait inferences. The correlation analysis is performed using only appearance, and the results from the experiments suggest that each trait is correlated with specific facial characteristics. | ||||
| Address | Florence, Italy | ||||
| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Andrea Fusiello, Vittorio Murino, Rita Cucchiara | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-33867-0 | Medium | |
| Area | Expedition | Conference | ECCVW | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | Admin @ si @ MTV2012 | Serial | 2171 | ||
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| Author | Fernando Vilariño; Petia Radeva | ||||
| Title | Cardiac Segmentation with Discriminant Active Contours | Type | Book Chapter | ||
| Year | 2003 | Publication | Abbreviated Journal | ||
| Volume | Issue | Pages |
211–217 | ||
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| Abstract | Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods. | ||||
| Address | Palma de Mallorca | ||||
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| Publisher | IOS Press | Place of Publication | Editor | ||
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| Area | Expedition | Conference | CCIA | ||
| Notes | MV;MILAB;SIAI | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 | Serial | 426 | ||
| Permanent link to this record | |||||
| Author | Ariel Amato; Felipe Lumbreras; Angel Sappa | ||||
| Title | A General-purpose Crowdsourcing Platform for Mobile Devices | Type | Conference Article | ||
| Year | 2014 | Publication | 9th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | 3 | Issue | Pages |
211-215 | |
| Keywords | Crowdsourcing Platform; Mobile Crowdsourcing | ||||
| Abstract | This paper presents details of a general purpose micro-task on-demand platform based on the crowdsourcing philosophy. This platform was specifically developed for mobile devices in order to exploit the strengths of such devices; namely: i) massivity, ii) ubiquity and iii) embedded sensors. The combined use of mobile platforms and the crowdsourcing model allows to tackle from the simplest to the most complex tasks. Users experience is the highlighted feature of this platform (this fact is extended to both task-proposer and tasksolver). Proper tools according with a specific task are provided to a task-solver in order to perform his/her job in a simpler, faster and appealing way. Moreover, a task can be easily submitted by just selecting predefined templates, which cover a wide range of possible applications. Examples of its usage in computer vision and computer games are provided illustrating the potentiality of the platform. | ||||
| Address | Lisboa; Portugal; January 2014 | ||||
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| Area | Expedition | Conference | VISAPP | ||
| Notes | ISE; ADAS; 600.054; 600.055; 600.076; 600.078 | Approved | no | ||
| Call Number | Admin @ si @ ALS2014 | Serial | 2478 | ||
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| Author | Cristina Palmero; Jordi Esquirol; Vanessa Bayo; Miquel Angel Cos; Pouya Ahmadmonfared; Joan Salabert; David Sanchez; Sergio Escalera | ||||
| Title | Automatic Sleep System Recommendation by Multi-modal RBG-Depth-Pressure Anthropometric Analysis | Type | Journal Article | ||
| Year | 2017 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV |
| Volume | 122 | Issue | 2 | Pages |
212–227 |
| Keywords | Sleep system recommendation; RGB-Depth data Pressure imaging; Anthropometric landmark extraction; Multi-part human body segmentation | ||||
| Abstract | This paper presents a novel system for automatic sleep system recommendation using RGB, depth and pressure information. It consists of a validated clinical knowledge-based model that, along with a set of prescription variables extracted automatically, obtains a personalized bed design recommendation. The automatic process starts by performing multi-part human body RGB-D segmentation combining GrabCut, 3D Shape Context descriptor and Thin Plate Splines, to then extract a set of anthropometric landmark points by applying orthogonal plates to the segmented human body. The extracted variables are introduced to the computerized clinical model to calculate body circumferences, weight, morphotype and Body Mass Index categorization. Furthermore, pressure image analysis is performed to extract pressure values and at-risk points, which are also introduced to the model to eventually obtain the final prescription of mattress, topper, and pillow. We validate the complete system in a set of 200 subjects, showing accurate category classification and high correlation results with respect to manual measures. | ||||
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| Notes | HuPBA;MILAB; 303.100 | Approved | no | ||
| Call Number | Admin @ si @ PEB2017 | Serial | 2765 | ||
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| Author | Debora Gil; Oriol Rodriguez-Leor; Petia Radeva; Aura Hernandez-Sabate | ||||
| Title | Assessing Artery Motion Compensation in IVUS | Type | Book Chapter | ||
| Year | 2007 | Publication | Computer Analysis Of Images And Patterns | Abbreviated Journal | LNCS |
| Volume | 4673 | Issue | Pages |
213-220 | |
| Keywords | validation standards; quality measures; IVUS motion compensation; conservation laws; Fourier development | ||||
| Abstract | Cardiac dynamics suppression is a main issue for visual improvement and computation of tissue mechanical properties in IntraVascular UltraSound (IVUS). Although in recent times several motion compensation techniques have arisen, there is a lack of objective evaluation of motion reduction in in vivo pullbacks. We consider that the assessment protocol deserves special attention for the sake of a clinical applicability as reliable as possible. Our work focuses on defining a quality measure and a validation protocol assessing IVUS motion compensation. On the grounds of continuum mechanics laws we introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; while results in in vivo pullbacks show its reliability in clinical cases. | ||||
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| Publisher | Springerlink | Place of Publication | Heidelberg | Editor | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-540-74271-5 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | IAM;MILAB | Approved | no | ||
| Call Number | IAM @ iam @ GRR2007 | Serial | 1540 | ||
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