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Author  |
Francesco Ciompi; Simone Balocco; Juan Rigla; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | Computer-Aided Detection of Intra-Coronary Stent in Intravascular Ultrasound Sequences | Type | Journal Article | ||
| Year | 2016 | Publication | Medical Physics | Abbreviated Journal | MP |
| Volume | 43 | Issue | 10 | Pages | |
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| Abstract | Purpose: An intraluminal coronary stent is a metal mesh tube deployed in a stenotic artery during Percutaneous Coronary Intervention (PCI), in order to prevent acute vessel occlusion. The identi cation of struts location and the de nition of the stent shape are relevant for PCI planning 15 and for patient follow-up. We present a fully-automatic framework for Computer-Aided Detection
(CAD) of intra-coronary stents in Intravascular Ultrasound (IVUS) image sequences. The CAD system is able to detect stent struts and estimate the stent shape. Methods: The proposed CAD uses machine learning to provide a comprehensive interpretation of the local structure of the vessel by means of semantic classi cation. The output of the classi cation 20 stage is then used to detect struts and to estimate the stent shape. The proposed approach is validated using a multi-centric data-set of 1,015 images from 107 IVUS sequences containing both metallic and bio-absorbable stents. Results: The method was able to detect structs in both metallic stents with an overall F-measure of 77.7% and a mean distance of 0.15 mm from manually annotated struts, and in bio-absorbable 25 stents with an overall F-measure of 77.4% and a mean distance of 0.09 mm from manually annotated struts. Conclusions: The results are close to the inter-observer variability and suggest that the system has the potential of being used as method for aiding percutaneous interventions. |
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ CBR2016 | Serial | 2819 | ||
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| Author |
Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva | ||||
| Title | Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images | Type | Conference Article | ||
| Year | 2013 | Publication | 16th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 8150 | Issue | 2 | Pages | 345-352 |
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| Abstract | We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm. | ||||
| Address | Nagoya; Japan; September 2013 | ||||
| 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 | 978-3-642-40762-8 | Medium | |
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ CBC2013 | Serial | 2258 | ||
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| Author |
Francesco Ciompi; Rui Hua; Simone Balocco; Marina Alberti; Oriol Pujol; Carles Caus; J. Mauri; Petia Radeva | ||||
| Title | Learning to Detect Stent Struts in Intravascular Ultrasound | Type | Conference Article | ||
| Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 7887 | Issue | Pages | 575-583 | |
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| Abstract | In this paper we tackle the automatic detection of struts elements (metallic braces of a stent device) in Intravascular Ultrasound (IVUS) sequences. The proposed method is based on context-aware classification of IVUS images, where we use Multi-Class Multi-Scale Stacked Sequential Learning (M2SSL). Additionally, we introduce a novel technique to reduce the amount of required contextual features. The comparison with binary and multi-class learning is also performed, using a dataset of IVUS images with struts manually annotated by an expert. The best performing configuration reaches a F-measure F = 63.97% . | ||||
| Address | Madeira; Portugal; June 2013 | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-642-38627-5 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | MILAB; HuPBA; 605.203; 600.046 | Approved | no | ||
| Call Number | Admin @ si @ CHB2013 | Serial | 2349 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | Automatic Key Frames Detection in Intravascular Ultrasound Sequences | Type | Conference Article | ||
| Year | 2011 | Publication | In MICCAI 2011 Workshop on Computing and Visualization for Intra Vascular Imaging | Abbreviated Journal | |
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| Abstract | We present a method for the automatic detection of key frames in Intravascular Ultrasound (IVUS) sequences. The key frames are markers delimiting morphological changes along the vessel. The aim of defining key frames is two-fold: (1) they allow to summarize the content of the pullback into few representative frames; (2) they represent the basis for the automatic detection of clinical events in IVUS. The proposed approach achieved a compression ratio of 0.016 with respect to the original sequence and an average inter-frame distance of 61.76 frame, minimizing the number of missed clinical events. | ||||
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| Area | Expedition | Conference | CVII | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPB2011 | Serial | 1767 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Petia Radeva | ||||
| Title | A meta-learning approach to Conditional Random Fields using Error-Correcting Output Codes | Type | Conference Article | ||
| Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 710–713 | ||
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| Abstract | We present a meta-learning framework for the design of potential functions for Conditional Random Fields. The design of both node potential and edge potential is formulated as a classification problem where margin classifiers are used. The set of state transitions for the edge potential is treated as a set of different classes, thus defining a multi-class learning problem. The Error-Correcting Output Codes (ECOC) technique is used to deal with the multi-class problem. Furthermore, the point defined by the combination of margin classifiers in the ECOC space is interpreted in a probabilistic manner, and the obtained distance values are then converted into potential values. The proposed model exhibits very promising results when applied to two real detection problems. | ||||
| Address | Istanbul;Turkey | ||||
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| ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
| Area | Expedition | Conference | ICPR | ||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2010a | Serial | 1365 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Petia Radeva | ||||
| Title | ECOC-DRF: Discriminative random fields based on error correcting output codes | Type | Journal Article | ||
| Year | 2014 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 47 | Issue | 6 | Pages | 2193-2204 |
| Keywords | Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models | ||||
| Abstract | We present ECOC-DRF, a framework where potential functions for Discriminative Random Fields are formulated as an ensemble of classifiers. We introduce the label trick, a technique to express transitions in the pairwise potential as meta-classes. This allows to independently learn any possible transition between labels without assuming any pre-defined model. The Error Correcting Output Codes matrix is used as ensemble framework for the combination of margin classifiers. We apply ECOC-DRF to a large set of classification problems, covering synthetic, natural and medical images for binary and multi-class cases, outperforming state-of-the art in almost all the experiments. | ||||
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| Notes | LAMP; HuPBA; MILAB; 605.203; 600.046; 601.043; 600.079 | Approved | no | ||
| Call Number | Admin @ si @ CPR2014b | Serial | 2470 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Carlo Gatta; Angel Serrano; Petia Radeva | ||||
| Title | Enhancing In-Vitro IVUS Data for Tissue Characterization | Type | Conference Article | ||
| Year | 2009 | Publication | 4th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
| Volume | 5524 | Issue | Pages | 241–248 | |
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| Abstract | Intravascular Ultrasound (IVUS) data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue, obtaining a reliable ground truth. The main drawback of this method is the few number of available study cases due to the complex procedure of histological analysis. In this work we propose a novel semi-supervised approach to enhance the in-vitro training set by including examples from in-vivo coronary plaques data set. For this purpose, a Sequential Floating Forward Selection method is applied on in-vivo data and plaque characterization performances are evaluated by Leave-One-Patient-Out cross-validation technique. Supervised data inclusion improves global classification accuracy from 89.39% to 91.82%. | ||||
| Address | Póvoa de Varzim, Portugal | ||||
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| 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 | 978-3-642-02171-8 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2009a | Serial | 1162 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Oriol Rodriguez-Leor; Angel Serrano; J. Mauri; Petia Radeva | ||||
| Title | On in-vitro and in-vivo IVUS data fusion | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
| Volume | 202 | Issue | Pages | 147-156 | |
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| Abstract | The design and the validation of an automatic plaque characterization technique based on Intravascular Ultrasound (IVUS) usually requires a data ground-truth. The histological analysis of post-mortem coronary arteries is commonly assumed as the state-of-the-art process for the extraction of a reliable data-set of atherosclerotic plaques. Unfortunately, the amount of data provided by this technique is usually few, due to the difficulties in collecting post-mortem cases and phenomena of tissue spoiling during histological analysis. In this paper we tackle the process of fusing in-vivo and in-vitro IVUS data starting with the analysis of recently proposed approaches for the creation of an enhanced IVUS data-set; furthermore, we propose a new approach, named pLDS, based on semi-supervised learning with a data selection criterion. The enhanced data-set obtained by each one of the analyzed approaches is used to train a classifier for tissue characterization purposes. Finally, the discriminative power of each classifier is quantitatively assessed and compared by classifying a data-set of validated in-vitro IVUS data. | ||||
| Address | Cardona (Spain) | ||||
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| ISSN | ISBN | 978-1-60750-061-2 | Medium | ||
| Area | Expedition | Conference | CCIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPR2009d | Serial | 1204 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva | ||||
| Title | ECOC Random Fields for Lumen Segmentation in Radial Artery IVUS Sequences | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference on Medical Image and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 5762 | Issue | II | Pages | |
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| Abstract | The measure of lumen volume on radial arteries can be used to evaluate the vessel response to different vasodilators. In this paper, we present a framework for automatic lumen segmentation in longitudinal cut images of radial artery from Intravascular ultrasound sequences. The segmentation is tackled as a classification problem where the contextual information is exploited by means of Conditional Random Fields (CRFs). A multi-class classification framework is proposed, and inference is achieved by combining binary CRFs according to the Error-Correcting-Output-Code technique. The results are validated against manually segmented sequences. Finally, the method is compared with other state-of-the-art classifiers. | ||||
| Address | London, UK | ||||
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| 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 | 978-3-642-04270-6 | Medium | |
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPF2009 | Serial | 1228 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva | ||||
| Title | Conditional Random Fields for image segmentation in Intravascular Ultrasound | Type | Conference Article | ||
| Year | 2010 | Publication | Medical Image Computing in Catalunya: Graduate Student Workshop | Abbreviated Journal | |
| Volume | Issue | Pages | 13–14 | ||
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| Abstract | We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved. | ||||
| Address | Girona | ||||
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| Area | Expedition | Conference | MICCAT | ||
| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPF2010 | Serial | 1453 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | A Holistic Approach for the Detection of Media-Adventitia Border in IVUS | Type | Conference Article | ||
| Year | 2011 | Publication | 14th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
| Volume | 6893 | Issue | Pages | 401-408 | |
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| Abstract | In this paper we present a methodology for the automatic detection of media-adventitia border (MAb) in Intravascular Ultrasound. A robust computation of the MAb is achieved through a holistic approach where the position of the MAb with respect to other tissues of the vessel is used. A learned quality measure assures that the resulting MAb is optimal with respect to all other tissues. The mean distance error computed through a set of 140 images is 0.2164 (±0.1326) mm. | ||||
| Address | Toronto, Canada | ||||
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| 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 | 978-3-642-23625-9 | Medium | |
| Area | Expedition | Conference | MICCAI | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPG2011 | Serial | 1739 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Oriol Rodriguez-Leor; J. Mauri; Petia Radeva | ||||
| Title | Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal of Cardiovascular Imaging | Abbreviated Journal | IJCI |
| Volume | 26 | Issue | 7 | Pages | 763–779 |
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| Abstract | Accurate detection of in-vivo vulnerable plaque in coronary arteries is still an open problem. Recent studies show that it is highly related to tissue structure and composition. Intravascular Ultrasound (IVUS) is a powerful imaging technique that gives a detailed cross-sectional image of the vessel, allowing to explore arteries morphology. IVUS data validation is usually performed by comparing post-mortem (in-vitro) IVUS data and corresponding histological analysis of the tissue. The main drawback of this method is the few number of available case studies and validated data due to the complex procedure of histological analysis of the tissue. On the other hand, IVUS data from in-vivo cases is easy to obtain but it can not be histologically validated. In this work, we propose to enhance the in-vitro training data set by selectively including examples from in-vivo plaques. For this purpose, a Sequential Floating Forward Selection method is reformulated in the context of plaque characterization. The enhanced classifier performance is validated on in-vitro data set, yielding an overall accuracy of 91.59% in discriminating among fibrotic, lipidic and calcified plaques, while reducing the gap between in-vivo and in-vitro data analysis. Experimental results suggest that the obtained classifier could be properly applied on in-vivo plaque characterization and also demonstrate that the common hypothesis of assuming the difference between in-vivo and in-vitro as negligible is incorrect. | ||||
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| ISSN | 1569-5794 | ISBN | Medium | ||
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| Notes | MILAB;HUPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CPG2010 | Serial | 1305 | ||
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| Author |
Francesco Ciompi; Oriol Pujol; Carlo Gatta; Marina Alberti; Simone Balocco; Xavier Carrillo; J. Mauri; Petia Radeva | ||||
| Title | HoliMab: A Holistic Approach for Media-Adventitia Border Detection in Intravascular Ultrasound | Type | Journal Article | ||
| Year | 2012 | Publication | Medical Image Analysis | Abbreviated Journal | MIA |
| Volume | 16 | Issue | 6 | Pages | 1085-1100 |
| Keywords | Media–Adventitia border detection; Intravascular ultrasound; Multi-Scale Stacked Sequential Learning; Error-correcting output codes; Holistic segmentation | ||||
| Abstract | We present a fully automatic methodology for the detection of the Media-Adventitia border (MAb) in human coronary artery in Intravascular Ultrasound (IVUS) images. A robust border detection is achieved by means of a holistic interpretation of the detection problem where the target object, i.e. the media layer, is considered as part of the whole vessel in the image and all the relationships between tissues are learnt. A fairly general framework exploiting multi-class tissue characterization as well as contextual information on the morphology and the appearance of the tissues is presented. The methodology is (i) validated through an exhaustive comparison with both Inter-observer variability on two challenging databases and (ii) compared with state-of-the-art methods for the detection of the MAb in IVUS. The obtained averaged values for the mean radial distance and the percentage of area difference are 0.211 mm and 10.1%, respectively. The applicability of the proposed methodology to clinical practice is also discussed. | ||||
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPG2012 | Serial | 1995 | ||
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| Author |
Francesco Ciompi; A. Palaioroutas; M. Loeve; Oriol Pujol; Petia Radeva; H. Tiddens; M. de Bruijne | ||||
| Title | Lung Tissue Classification in Severe Advanced Cystic Fibrosis from CT Scans | Type | Conference Article | ||
| Year | 2011 | Publication | In MICCAI 2011 4th International Workshop on Pulmonary Image Analysis | Abbreviated Journal | |
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| Address | Toronto, Canada | ||||
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| Area | Expedition | Conference | PIA | ||
| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | Admin @ si @ CPL2011 | Serial | 1798 | ||
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| Author |
Francesco Ciompi | ||||
| Title | ECOC-based Plaque Classification using In-vivo and Exvivo Intravascular Ultrasound Data | Type | Miscellaneous | ||
| Year | 2008 | Publication | CVC Technical Report #125 | Abbreviated Journal | |
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| Address | Bellaterra (Spain) | ||||
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| Notes | Approved | no | |||
| Call Number | Admin @ si @ Cio2008 | Serial | 1145 | ||
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