Home | [171–180] << 181 182 183 184 185 186 187 188 189 190 >> [191–200] |
Records | |||||
---|---|---|---|---|---|
Author | Muhammad Anwer Rao; Fahad Shahbaz Khan; Joost Van de Weijer; Jorma Laaksonen | ||||
Title | Combining Holistic and Part-based Deep Representations for Computational Painting Categorization | Type | Conference Article | ||
Year | 2016 | Publication | 6th International Conference on Multimedia Retrieval | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | Automatic analysis of visual art, such as paintings, is a challenging inter-disciplinary research problem. Conventional approaches only rely on global scene characteristics by encoding holistic information for computational painting categorization.We argue that such approaches are sub-optimal and that discriminative common visual structures provide complementary information for painting classification. We present an approach that encodes both the global scene layout and discriminative latent common structures for computational painting categorization. The region of interests are automatically extracted, without any manual part labeling, by training class-specific deformable part-based models. Both holistic and region-of-interests are then described using multi-scale dense convolutional features. These features are pooled separately using Fisher vector encoding and concatenated afterwards in a single image representation. Experiments are performed on a challenging dataset with 91 different painters and 13 diverse painting styles. Our approach outperforms the standard method, which only employs the global scene characteristics. Furthermore, our method achieves state-of-the-art results outperforming a recent multi-scale deep features based approach [11] by 6.4% and 3.8% respectively on artist and style classification. | ||||
Address | New York; USA; June 2016 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICMR | ||
Notes | LAMP; 600.068; 600.079;ADAS | Approved | no | ||
Call Number | Admin @ si @ RKW2016 | Serial | 2763 | ||
Permanent link to this record | |||||
Author | Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas | ||||
Title | A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention | Type | Conference Article | ||
Year | 2016 | Publication | AutoML Workshop | Abbreviated Journal | |
Volume | Issue | 1 | Pages | 1-8 | |
Keywords | AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning | ||||
Abstract | The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML. | ||||
Address | New York; USA; June 2016 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICML | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GCE2016 | Serial | 2769 | ||
Permanent link to this record | |||||
Author | Marc Masana; Idoia Ruiz; Joan Serrat; Joost Van de Weijer; Antonio Lopez | ||||
Title | Metric Learning for Novelty and Anomaly Detection | Type | Conference Article | ||
Year | 2018 | Publication | 29th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | When neural networks process images which do not resemble the distribution seen during training, so called out-of-distribution images, they often make wrong predictions, and do so too confidently. The capability to detect out-of-distribution images is therefore crucial for many real-world applications. We divide out-of-distribution detection between novelty detection ---images of classes which are not in the training set but are related to those---, and anomaly detection ---images with classes which are unrelated to the training set. By related we mean they contain the same type of objects, like digits in MNIST and SVHN. Most existing work has focused on anomaly detection, and has addressed this problem considering networks trained with the cross-entropy loss. Differently from them, we propose to use metric learning which does not have the drawback of the softmax layer (inherent to cross-entropy methods), which forces the network to divide its prediction power over the learned classes. We perform extensive experiments and evaluate both novelty and anomaly detection, even in a relevant application such as traffic sign recognition, obtaining comparable or better results than previous works. | ||||
Address | Newcastle; uk; September 2018 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | BMVC | ||
Notes | LAMP; ADAS; 601.305; 600.124; 600.106; 602.200; 600.120; 600.118 | Approved | no | ||
Call Number | Admin @ si @ MRS2018 | Serial | 3156 | ||
Permanent link to this record | |||||
Author | Cristina Palmero; Javier Selva; Mohammad Ali Bagheri; Sergio Escalera | ||||
Title | Recurrent CNN for 3D Gaze Estimation using Appearance and Shape Cues | Type | Conference Article | ||
Year | 2018 | Publication | 29th British Machine Vision Conference | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | Gaze behavior is an important non-verbal cue in social signal processing and humancomputer interaction. In this paper, we tackle the problem of person- and head poseindependent 3D gaze estimation from remote cameras, using a multi-modal recurrent convolutional neural network (CNN). We propose to combine face, eyes region, and face landmarks as individual streams in a CNN to estimate gaze in still images. Then, we exploit the dynamic nature of gaze by feeding the learned features of all the frames in a sequence to a many-to-one recurrent module that predicts the 3D gaze vector of the last frame. Our multi-modal static solution is evaluated on a wide range of head poses and gaze directions, achieving a significant improvement of 14.6% over the state of the art on
EYEDIAP dataset, further improved by 4% when the temporal modality is included. |
||||
Address | Newcastle; UK; September 2018 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | BMVC | ||
Notes | HUPBA; no proj | Approved | no | ||
Call Number | Admin @ si @ PSB2018 | Serial | 3208 | ||
Permanent link to this record | |||||
Author | Alex Falcon; Swathikiran Sudhakaran; Giuseppe Serra; Sergio Escalera; Oswald Lanz | ||||
Title | Relevance-based Margin for Contrastively-trained Video Retrieval Models | Type | Conference Article | ||
Year | 2022 | Publication | ICMR '22: Proceedings of the 2022 International Conference on Multimedia Retrieval | Abbreviated Journal | |
Volume | Issue | Pages | 146-157 | ||
Keywords | |||||
Abstract | Video retrieval using natural language queries has attracted increasing interest due to its relevance in real-world applications, from intelligent access in private media galleries to web-scale video search. Learning the cross-similarity of video and text in a joint embedding space is the dominant approach. To do so, a contrastive loss is usually employed because it organizes the embedding space by putting similar items close and dissimilar items far. This framework leads to competitive recall rates, as they solely focus on the rank of the groundtruth items. Yet, assessing the quality of the ranking list is of utmost importance when considering intelligent retrieval systems, since multiple items may share similar semantics, hence a high relevance. Moreover, the aforementioned framework uses a fixed margin to separate similar and dissimilar items, treating all non-groundtruth items as equally irrelevant. In this paper we propose to use a variable margin: we argue that varying the margin used during training based on how much relevant an item is to a given query, i.e. a relevance-based margin, easily improves the quality of the ranking lists measured through nDCG and mAP. We demonstrate the advantages of our technique using different models on EPIC-Kitchens-100 and YouCook2. We show that even if we carefully tuned the fixed margin, our technique (which does not have the margin as a hyper-parameter) would still achieve better performance. Finally, extensive ablation studies and qualitative analysis support the robustness of our approach. Code will be released at \urlhttps://github.com/aranciokov/RelevanceMargin-ICMR22. | ||||
Address | Newwark, NJ, USA, 27 June 2022 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICMR | ||
Notes | HuPBA; no menciona | Approved | no | ||
Call Number | Admin @ si @ FSS2022 | Serial | 3808 | ||
Permanent link to this record | |||||
Author | Jialuo Chen; Pau Riba; Alicia Fornes; Juan Mas; Josep Llados; Joana Maria Pujadas-Mora | ||||
Title | Word-Hunter: A Gamesourcing Experience to Validate the Transcription of Historical Manuscripts | Type | Conference Article | ||
Year | 2018 | Publication | 16th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 528-533 | ||
Keywords | Crowdsourcing; Gamification; Handwritten documents; Performance evaluation | ||||
Abstract | Nowadays, there are still many handwritten historical documents in archives waiting to be transcribed and indexed. Since manual transcription is tedious and time consuming, the automatic transcription seems the path to follow. However, the performance of current handwriting recognition techniques is not perfect, so a manual validation is mandatory. Crowdsourcing is a good strategy for manual validation, however it is a tedious task. In this paper we analyze experiences based in gamification
in order to propose and design a gamesourcing framework that increases the interest of users. Then, we describe and analyze our experience when validating the automatic transcription using the gamesourcing application. Moreover, thanks to the combination of clustering and handwriting recognition techniques, we can speed up the validation while maintaining the performance. |
||||
Address | Niagara Falls, USA; August 2018 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICFHR | ||
Notes | DAG; 600.097; 603.057; 600.121 | Approved | no | ||
Call Number | Admin @ si @ CRF2018 | Serial | 3169 | ||
Permanent link to this record | |||||
Author | Anna Salvatella; Maria Vanrell; Juan J. Villanueva | ||||
Title | Texture Description based on Subtexture Components, 3rd International Workshop on Texture Syntesis and Analysis | Type | Conference Article | ||
Year | 2003 | Publication | 3rd International Workshop on Texture Synthesis and Analysis, | Abbreviated Journal | |
Volume | Issue | Pages | 77–82 | ||
Keywords | |||||
Abstract | |||||
Address | Nice | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 1-904410-11-1 | Medium | ||
Area | Expedition | Conference | |||
Notes | CIC | Approved | no | ||
Call Number | CAT @ cat @ SVV2003 | Serial | 422 | ||
Permanent link to this record | |||||
Author | Angel Sappa; Fadi Dornaika; David Geronimo; Antonio Lopez | ||||
Title | Registration-based Moving Object Detection from a Moving Camera | Type | Conference Article | ||
Year | 2008 | Publication | IROS2008 2nd Workshop on Perception, Planning and Navigation for Intelligent Vehicles | Abbreviated Journal | |
Volume | Issue | Pages | 65–69 | ||
Keywords | |||||
Abstract | This paper presents a robust approach for detecting moving objects from on-board stereo vision systems. It relies on a feature point quaternion-based registration, which avoids common problems that appear when computationally expensive iterative-based algorithms are used on dynamic environments. The proposed approach consists of three stages. Initially, feature points are extracted and tracked through consecutive frames. Then, a RANSAC based approach is used for registering
two 3D point sets with known correspondences by means of the quaternion method. Finally, the computed 3D rigid displacement is used to map two consecutive frames into the same coordinate system. Moving objects correspond to those areas with large registration errors. Experimental results, in different scenarios, show the viability of the proposed approach. |
||||
Address | Nice (France) | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | |||
Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ SDG2008 | Serial | 1017 | ||
Permanent link to this record | |||||
Author | Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi | ||||
Title | Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging | Type | Conference Article | ||
Year | 2009 | Publication | 5th International Conference on Functional Imaging and Modeling of the Heart | Abbreviated Journal | |
Volume | 5528 | Issue | Pages | 330–338 | |
Keywords | |||||
Abstract | In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm). | ||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-01931-9 | Medium | |
Area | Expedition | Conference | FIMH | ||
Notes | MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ COP2009 | Serial | 1255 | ||
Permanent link to this record | |||||
Author | Ferran Poveda; Debora Gil;Enric Marti | ||||
Title | Multi-resolution DT-MRI cardiac tractography | Type | Conference Article | ||
Year | 2012 | Publication | Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges | Abbreviated Journal | |
Volume | 7746 | Issue | Pages | 270-277 | |
Keywords | |||||
Abstract | Even using objective measures from DT-MRI no consensus about myocardial architecture has been achieved so far. Streamlining provides good reconstructions at low level of detail, but falls short to give global abstract interpretations. In this paper, we present a multi-resolution methodology that is able to produce simplified representations of cardiac architecture. Our approach produces a reduced set of tracts that are representative of the main geometric features of myocardial anatomical structure. Experiments show that fiber geometry is preserved along reductions, which validates the simplified model for interpretation of cardiac architecture. | ||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-36960-5 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ PGM2012 | Serial | 1986 | ||
Permanent link to this record | |||||
Author | Debora Gil;Agnes Borras;Ruth Aris;Mariano Vazquez;Pierre Lafortune; Guillame Houzeaux | ||||
Title | What a difference in biomechanics cardiac fiber makes | Type | Conference Article | ||
Year | 2012 | Publication | Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges | Abbreviated Journal | |
Volume | 7746 | Issue | Pages | 253-260 | |
Keywords | |||||
Abstract | Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle. |
||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-36960-5 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ GBA2012 | Serial | 1987 | ||
Permanent link to this record | |||||
Author | Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil | ||||
Title | Optimal Medial Surface Generation for Anatomical Volume Representations | Type | Book Chapter | ||
Year | 2012 | Publication | Abdominal Imaging. Computational and Clinical Applications | Abbreviated Journal | LNCS |
Volume | 7601 | Issue | Pages | 265-273 | |
Keywords | Medial surface representation; volume reconstruction | ||||
Abstract | Medial representations are a widely used technique in abdominal organ shape representation and parametrization. Those methods require good medial manifolds as a starting point. Any medial
surface used to parametrize a volume should be simple enough to allow an easy manipulation and complete enough to allow an accurate reconstruction of the volume. Obtaining good quality medial surfaces is still a problem with current iterative thinning methods. This forces the usage of generic, pre-calculated medial templates that are adapted to the final shape at the cost of a drop in volume reconstruction. This paper describes an operator for generation of medial structures that generates clean and complete manifolds well suited for their further use in medial representations of abdominal organ volumes. While being simpler than thinning surfaces, experiments show its high performance in volume reconstruction and preservation of medial surface main branching topology. |
||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | Yoshida, Hiroyuki and Hawkes, David and Vannier, MichaelW. | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Lecture Notes in Computer Science | Abbreviated Series Title | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-33611-9 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | IAM | Approved | no | ||
Call Number | IAM @ iam @ VGG2012b | Serial | 1988 | ||
Permanent link to this record | |||||
Author | Simeon Petkov; Adriana Romero; Xavier Carrillo; Petia Radeva; Carlo Gatta | ||||
Title | Robust and accurate diaphragm border detection in cardiac X-Ray angiographies | Type | Conference Article | ||
Year | 2012 | Publication | Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges | Abbreviated Journal | |
Volume | 7746 | Issue | Pages | 225-234 | |
Keywords | |||||
Abstract | Workshop STACOM, dins del MICCAI
X-ray angiography is the most common imaging modality employed in the diagnosis of coronary diseases prior to or during a catheter-based intervention. The analysis of the patient X-Ray sequence can provide useful information about the degree of arterial stenosis, the myocardial perfusion and other clinical parameters. If the sequence has been acquired to evaluate the perfusion grade, the opacity due to the diaphragm could potentially hinder any kind of visual inspection and make more difficult a computer aided measurements. In this paper we propose an accurate and robust method to automatically identify the diaphragm border in each frame. Quantitative evaluation on a set of 11 sequences shows that the proposed algorithm outperforms previous methods. |
||||
Address | Nice, France | ||||
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 | 0302-9743 | ISBN | 978-3-642-36960-5 | Medium | |
Area | Expedition | Conference | STACOM | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ PRC2012 | Serial | 2028 | ||
Permanent link to this record | |||||
Author | Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru | ||||
Title | Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs | Type | Conference Article | ||
Year | 2011 | Publication | Workshop on Computational and Clinical Applications in Abdominal Imaging | Abbreviated Journal | |
Volume | 7029 | Issue | Pages | 223-230 | |
Keywords | |||||
Abstract | Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations. | ||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | In H. Yoshida et al | |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ABDI | ||
Notes | IAM; MV | Approved | no | ||
Call Number | VGB2011 | Serial | 2036 | ||
Permanent link to this record | |||||
Author | Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
Title | Automatic Non-Rigid Temporal Alignment of IVUS Sequences | Type | Conference Article | ||
Year | 2012 | Publication | 15th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | 1 | Issue | Pages | 642-650 | |
Keywords | |||||
Abstract | Clinical studies on atherosclerosis regression/progression performed by Intravascular Ultrasound analysis require the alignment of pullbacks of the same patient before and after clinical interventions. In this paper, a methodology for the automatic alignment of IVUS sequences based on the Dynamic Time Warping technique is proposed. The method is adapted to the specific IVUS alignment task by applying the non-rigid alignment technique to multidimensional morphological signals, and by introducing a sliding window approach together with a regularization term. To show the effectiveness of our method, an extensive validation is performed both on synthetic data and in-vivo IVUS sequences. The proposed method is robust to stent deployment and post dilation surgery and reaches an alignment error of approximately 0.7 mm for in-vivo data, which is comparable to the inter-observer variability. | ||||
Address | Nice, France | ||||
Corporate Author | Thesis | ||||
Publisher | Springer-Verlag Berlin, Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-3-642-33414-6 | Medium | ||
Area | Expedition | Conference | MICCAI | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ ABC2012 | Serial | 2168 | ||
Permanent link to this record |