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Author |
Francesco Ciompi |
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Title |
Multi-Class Learning for Vessel Characterization in Intravascular Ultrasound |
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2012 |
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PhD Thesis, Universitat de Barcelona-CVC |
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In this thesis we tackle the problem of automatic characterization of human coronary vessel in Intravascular Ultrasound (IVUS) image modality. The basis for the whole characterization process is machine learning applied to multi-class problems. In all the presented approaches, the Error-Correcting Output Codes (ECOC) framework is used as central element for the design of multi-class classifiers.
Two main topics are tackled in this thesis. First, the automatic detection of the vessel borders is presented. For this purpose, a novel context-aware classifier for multi-class classification of the vessel morphology is presented, namely ECOC-DRF. Based on ECOC-DRF, the lumen border and the media-adventitia border in IVUS are robustly detected by means of a novel holistic approach, achieving an error comparable with inter-observer variability and with state of the art methods.
The two vessel borders define the atheroma area of the vessel. In this area, tissue characterization is required. For this purpose, we present a framework for automatic plaque characterization by processing both texture in IVUS images and spectral information in raw Radio Frequency data. Furthermore, a novel method for fusing in-vivo and in-vitro IVUS data for plaque characterization is presented, namely pSFFS. The method demonstrates to effectively fuse data generating a classifier that improves the tissue characterization in both in-vitro and in-vivo datasets.
A novel method for automatic video summarization in IVUS sequences is also presented. The method aims to detect the key frames of the sequence, i.e., the frames representative of morphological changes. This novel method represents the basis for video summarization in IVUS as well as the markers for the partition of the vessel into morphological and clinically interesting events.
Finally, multi-class learning based on ECOC is applied to lung tissue characterization in Computed Tomography. The novel proposed approach, based on supervised and unsupervised learning, achieves accurate tissue classification on a large and heterogeneous dataset. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Petia Radeva;Oriol Pujol |
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MILAB |
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no |
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Admin @ si @ Cio2012 |
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2146 |
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Author |
Antonio Hernandez; Miguel Reyes; Victor Ponce; Sergio Escalera |
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Title |
GrabCut-Based Human Segmentation in Video Sequences |
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Journal Article |
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Year |
2012 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
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Volume |
12 |
Issue |
11 |
Pages |
15376-15393 |
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Keywords |
segmentation; human pose recovery; GrabCut; GraphCut; Active Appearance Models; Conditional Random Field |
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In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. |
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HuPBA;MILAB |
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no |
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Admin @ si @ HRP2012 |
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2147 |
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Petia Radeva; Michal Drozdzal; Santiago Segui; Laura Igual; Carolina Malagelada; Fernando Azpiroz; Jordi Vitria |
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Title |
Active labeling: Application to wireless endoscopy analysis |
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Conference Article |
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Year |
2012 |
Publication |
High Performance Computing and Simulation, International Conference on |
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174-181 |
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Today, robust learners trained in a real supervised machine learning application should count with a rich collection of positive and negative examples. Although in many applications, it is not difficult to obtain huge amount of data, labeling those data can be a very expensive process, especially when dealing with data of high variability and complexity. A good example of such cases are data from medical imaging applications where annotating anomalies like tumors, polyps, atherosclerotic plaque or informative frames in wireless endoscopy need highly trained experts. Building a representative set of training data from medical videos (e.g. Wireless Capsule Endoscopy) means that thousands of frames to be labeled by an expert. It is quite normal that data in new videos come different and thus are not represented by the training set. In this paper, we review the main approaches on active learning and illustrate how active learning can help to reduce expert effort in constructing the training sets. We show that applying active learning criteria, the number of human interventions can be significantly reduced. The proposed system allows the annotation of informative/non-informative frames of Wireless Capsule Endoscopy video containing more than 30000 frames each one with less than 100 expert ”clicks”. |
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978-1-4673-2359-8 |
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HPCS |
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MILAB; OR;MV |
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no |
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Admin @ si @ RDS2012 |
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2152 |
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Author |
Cristhian Aguilera; Fernando Barrera; Felipe Lumbreras; Angel Sappa; Ricardo Toledo |
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Title |
Multispectral Image Feature Points |
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Journal Article |
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Year |
2012 |
Publication |
Sensors |
Abbreviated Journal |
SENS |
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Volume |
12 |
Issue |
9 |
Pages |
12661-12672 |
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Keywords |
multispectral image descriptor; color and infrared images; feature point descriptor |
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Abstract |
Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art. |
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ADAS |
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no |
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Admin @ si @ ABL2012 |
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2154 |
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Author |
Cristhian Aguilera; M.Ramos; Angel Sappa |
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Title |
Simulated Annealing: A Novel Application of Image Processing in the Wood Area |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Simulated Annealing – Advances, Applications and Hybridizations |
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91-104 |
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Marcos de Sales Guerra Tsuzuki |
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978-953-51-0710-1 |
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ADAS |
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no |
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Admin @ si @ ARS2012 |
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2156 |
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Author |
Miguel Oliveira; V.Santos; Angel Sappa |
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Title |
Short term path planning using a multiple hypothesis evaluation approach for an autonomous driving competition |
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Conference Article |
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2012 |
Publication |
IEEE 4th Workshop on Planning, Perception and Navigation for Intelligent Vehicles |
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Algarve; Portugal |
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PPNIV |
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ADAS |
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no |
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Admin @ si @ OSS2012c |
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2159 |
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Author |
Marina Alberti; Simone Balocco; Xavier Carrillo; Josepa Mauri; Petia Radeva |
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Title |
Automatic Non-Rigid Temporal Alignment of IVUS Sequences |
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Conference Article |
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Year |
2012 |
Publication |
15th International Conference on Medical Image Computing and Computer Assisted Intervention |
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1 |
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642-650 |
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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. |
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Nice, France |
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Springer-Verlag Berlin, Heidelberg |
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978-3-642-33414-6 |
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MICCAI |
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MILAB |
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no |
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Call Number |
Admin @ si @ ABC2012 |
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2168 |
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Author |
Onur Ferhat |
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Title |
Eye-Tracking with Webcam-Based Setups: Implementation of a Real-Time System and an Analysis of Factors Affecting Performance |
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Report |
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2012 |
Publication |
CVC Technical Report |
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172 |
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Computer vision, eye-tracking, gaussian process, feature selection, optical flow |
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Abstract |
In the recent years commercial eye-tracking hardware has become more common, with the introduction of new models from several brands that have better performance and easier setup procedures. A cause and at the same time a result of this phenomenon is the popularity of eye-tracking research directed at marketing, accessibility and usability, among others.
One problem with these hardware components is scalability, because both the price and the necessary expertise to operate them makes it practically impossible in the large scale. In this work, we analyze the feasibility of a software eye-tracking system based on a single, ordinary webcam. Our aim is to discover the limits of such a system and to see whether it provides acceptable performances.
The significance of this setup is that it is the most common setup found in consumer environments, off-the-shelf electronic devices such as laptops, mobile phones and tablet computers. As no special equipment such as infrared lights, mirrors or zoom lenses are used; setting up and calibrating the system is easier compared to other approaches using these components.
Our work is based on the open source application Opengazer, which provides a good starting point for our contributions. We propose several improvements in order to push the system's performance further and make it feasible as a robust, real-time device. Then we carry out an elaborate experiment involving 18 human subjects and 4 different system setups. Finally, we give an analysis of the results and discuss the effects of setup changes, subject differences and modifications in the software. |
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Bellaterra |
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Corporate Author |
Computer Vision Center |
Thesis |
Master's thesis |
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Fernando Vilariño |
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MV |
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no |
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Admin @ si @ Fer2012; IAM @ iam @ Fer2012 |
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2165 |
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Author |
Pedro Martins; Paulo Carvalho; Carlo Gatta |
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Title |
Stable Salient Shapes |
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Conference Article |
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2012 |
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International Conference on Digital Image Computing: Techniques and Applications |
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DICTA |
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MILAB |
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no |
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Admin @ si @ MCG2012b |
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2166 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke; Alicia Fornes |
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Title |
On the Correlation of Graph Edit Distance and L1 Distance in the Attribute Statistics Embedding Space |
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Conference Article |
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2012 |
Publication |
Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshop |
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7626 |
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135-143 |
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Abstract |
Graph embeddings in vector spaces aim at assigning a pattern vector to every graph so that the problems of graph classification and clustering can be solved by using data processing algorithms originally developed for statistical feature vectors. An important requirement graph features should fulfil is that they reproduce as much as possible the properties among objects in the graph domain. In particular, it is usually desired that distances between pairs of graphs in the graph domain closely resemble those between their corresponding vectorial representations. In this work, we analyse relations between the edit distance in the graph domain and the L1 distance of the attribute statistics based embedding, for which good classification performance has been reported on various datasets. We show that there is actually a high correlation between the two kinds of distances provided that the corresponding parameter values that account for balancing the weight between node and edge based features are properly selected. |
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Springer-Berlag, Berlin |
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LNCS |
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978-3-642-34165-6 |
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SSPR&SPR |
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DAG |
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Admin @ si @ GVB2012c |
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2167 |
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Author |
Rui Hua; Oriol Pujol; Francesco Ciompi; Marina Alberti; Simone Balocco; Josepa Mauri; Petia Radeva |
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Stent Strut Detection by Classifying a Wide Set of IVUS Features |
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2012 |
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Computed Assisted Stenting Workshop |
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Nice, France |
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STENT |
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MILAB;HuPBA |
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Admin @ si @ HPC2012 |
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2169 |
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Simone Balocco; Carlo Gatta; Marina Alberti; Xavier Carrillo; Juan Rigla; Petia Radeva |
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Relation between plaque type, plaque thickness, blood shear stress and plaque stress in coronary arteries assessed by X-ray Angiography and Intravascular Ultrasound |
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2012 |
Publication |
Medical Physics |
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MEDPHYS |
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39 |
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12 |
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7430-7445 |
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Abstract |
PMID 23231293
PURPOSE:
Atheromatic plaque progression is affected, among others phenomena, by biomechanical, biochemical, and physiological factors. In this paper, the authors introduce a novel framework able to provide both morphological (vessel radius, plaque thickness, and type) and biomechanical (wall shear stress and Von Mises stress) indices of coronary arteries.
METHODS:
First, the approach reconstructs the three-dimensional morphology of the vessel from intravascular ultrasound (IVUS) and Angiographic sequences, requiring minimal user interaction. Then, a computational pipeline allows to automatically assess fluid-dynamic and mechanical indices. Ten coronary arteries are analyzed illustrating the capabilities of the tool and confirming previous technical and clinical observations.
RESULTS:
The relations between the arterial indices obtained by IVUS measurement and simulations have been quantitatively analyzed along the whole surface of the artery, extending the analysis of the coronary arteries shown in previous state of the art studies. Additionally, for the first time in the literature, the framework allows the computation of the membrane stresses using a simplified mechanical model of the arterial wall.
CONCLUSIONS:
Circumferentially (within a given frame), statistical analysis shows an inverse relation between the wall shear stress and the plaque thickness. At the global level (comparing a frame within the entire vessel), it is observed that heavy plaque accumulations are in general calcified and are located in the areas of the vessel having high wall shear stress. Finally, in their experiments the inverse proportionality between fluid and structural stresses is observed. |
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MILAB |
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no |
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Admin @ si @BGA2012 |
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2170 |
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Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
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Evaluation of Intrinsic Image Algorithms to Detect the Shadows Cast by Static Objects Outdoors |
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Journal Article |
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Year |
2012 |
Publication |
Sensors |
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SENS |
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12 |
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10 |
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13333-13348 |
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In some automatic scene analysis applications, the presence of shadows becomes a nuisance that is necessary to deal with. As a consequence, a preliminary stage in many computer vision algorithms is to attenuate their effect. In this paper, we focus our attention on the detection of shadows cast by static objects outdoors, as the scene is viewed for extended periods of time (days, weeks) from a fixed camera and considering daylight intervals where the main source of light is the sun. In this context, we report two contributions. First, we introduce the use of synthetic images for which ground truth can be generated automatically, avoiding the tedious effort of manual annotation. Secondly, we report a novel application of the intrinsic image concept to the automatic detection of shadows cast by static objects in outdoors. We make both a quantitative and a qualitative evaluation of several algorithms based on this image representation. For the quantitative evaluation, we used the synthetic data set, while for the qualitative evaluation we used both data sets. Our experimental results show that the evaluated methods can partially solve the problem of shadow detection. |
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Admin @ si @ ISR2012b |
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2173 |
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Xavier Otazu; Olivier Penacchio; Laura Dempere-Marco |
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Brightness induction by contextual influences in V1: a neurodynamical account |
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2012 |
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Journal of Vision |
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VSS |
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12 |
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9 |
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Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas and reveals fundamental properties of neural organization in the visual system. Several phenomenological models have been proposed that successfully account for psychophysical data (Pessoa et al. 1995, Blakeslee and McCourt 2004, Barkan et al. 2008, Otazu et al. 2008).
Neurophysiological evidence suggests that brightness information is explicitly represented in V1 and neuronal response modulations have been observed followingluminance changes outside their receptive fields (Rossi and Paradiso, 1999).
In this work we investigate possible neural mechanisms that offer a plausible explanation for such effects. To this end, we consider the model by Z.Li (1999) which is based on biological data and focuses on the part of V1 responsible for contextual influences, namely, layer 2–3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has proven to account for phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant effect of contextual influences. In our model, the input to the network is derived from a complete multiscale and multiorientation wavelet decomposition which makes it possible to recover an image reflecting the perceived intensity. The proposed model successfully accounts for well known pyschophysical effects (among them: the White's and modified White's effects, the Todorović, Chevreul, achromatic ring patterns, and grating induction effects). Our work suggests that intra-cortical interactions in the primary visual cortex could partially explain perceptual brightness induction effects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual pathway. |
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Admin @ si @ OPD2012b |
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2178 |
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Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu |
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Switching off brightness induction through induction-reversed images |
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2012 |
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Perception |
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PER |
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41 |
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208 |
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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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Admin @ si @ PDO2012a |
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2180 |
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