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Francesco Ciompi; Oriol Pujol; Petia Radeva |
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ECOC-DRF: Discriminative random fields based on error correcting output codes |
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2014 |
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Pattern Recognition |
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PR |
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47 |
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6 |
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2193-2204 |
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Discriminative random fields; Error-correcting output codes; Multi-class classification; Graphical models |
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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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LAMP; HuPBA; MILAB; 605.203; 600.046; 601.043; 600.079 |
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Admin @ si @ CPR2014b |
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2470 |
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Author |
Frederic Sampedro; Anna Domenech; Sergio Escalera |
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Static and dynamic computational cancer spread quantification in whole body FDG-PET/CT scans |
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2014 |
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Journal of Medical Imaging and Health Informatics |
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JMIHI |
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4 |
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6 |
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825-831 |
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CANCER SPREAD; COMPUTER AIDED DIAGNOSIS; MEDICAL IMAGING; TUMOR QUANTIFICATION |
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In this work we address the computational cancer spread quantification scenario in whole body FDG-PET/CT scans. At the static level, this setting can be modeled as a clustering problem on the set of 3D connected components of the whole body PET tumoral segmentation mask carried out by nuclear medicine physicians. At the dynamic level, and ad-hoc algorithm is proposed in order to quantify the cancer spread time evolution which, when combined with other existing indicators, gives rise to the metabolic tumor volume-aggressiveness-spread time evolution chart, a novel tool that we claim that would prove useful in nuclear medicine and oncological clinical or research scenarios. Good performance results of the proposed methodologies both at the clinical and technological level are shown using a dataset of 48 segmented whole body FDG-PET/CT scans. |
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HuPBA;MILAB |
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Admin @ si @ SDE2014b |
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2548 |
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Carolina Malagelada; Michal Drozdzal; Santiago Segui; Sara Mendez; Jordi Vitria; Petia Radeva; Javier Santos; Anna Accarino; Juan R. Malagelada; Fernando Azpiroz |
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Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis |
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2015 |
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American Journal of Physiology-Gastrointestinal and Liver Physiology |
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AJPGI |
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309 |
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6 |
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G413--G419 |
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capsule endoscopy; computer vision analysis; functional bowel disorders; intestinal motility; machine learning |
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We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function. |
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American Physiological Society |
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MILAB; OR;MV |
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Admin @ si @ MDS2015 |
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2666 |
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C. Butakoff; Simone Balocco; F.M. Sukno; C. Hoogendoorn; C. Tobon-Gomez; G. Avegliano; A.F. Frangi |
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Left-ventricular Epi- and Endocardium Extraction from 3D Ultrasound Images Using an Automatically Constructed 3D ASM |
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2016 |
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Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
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CMBBE |
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4 |
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5 |
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265-280 |
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ASM; cardiac segmentation; statistical model; shape model; 3D ultrasound; cardiac segmentation |
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In this paper, we propose an automatic method for constructing an active shape model (ASM) to segment the complete cardiac left ventricle in 3D ultrasound (3DUS) images, which avoids costly manual landmarking. The automatic construction of the ASM has already been addressed in the literature; however, the direct application of these methods to 3DUS is hampered by a high level of noise and artefacts. Therefore, we propose to construct the ASM by fusing the multidetector computed tomography data, to learn the shape, with the artificially generated 3DUS, in order to learn the neighbourhood of the boundaries. Our artificial images were generated by two approaches: a faster one that does not take into account the geometry of the transducer, and a more comprehensive one, implemented in Field II toolbox. The segmentation accuracy of our ASM was evaluated on 20 patients with left-ventricular asynchrony, demonstrating plausibility of the approach. |
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2168-1163 |
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MILAB |
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Admin @ si @ BBS2016 |
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2449 |
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Author |
Debora Gil; Oriol Rodriguez-Leon; Petia Radeva; Josepa Mauri |
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Title |
Myocardial Perfusion Characterization From Contrast Angiography Spectral Distribution |
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2008 |
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IEEE Transactions on Medical Imaging |
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27 |
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5 |
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641-649 |
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Contrast angiography; myocardial perfusion; spectral analysis. |
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Despite recovering a normal coronary flow after acute myocardial infarction, percutaneous coronary intervention does not guarantee a proper perfusion (irrigation) of the infarcted area. This damage in microcirculation integrity may detrimentally affect the patient survival. Visual assessment of the myocardium opacification in contrast angiography serves to define a subjective score of the microcirculation integrity myocardial blush analysis (MBA). Although MBA correlates with patient prognosis its visual assessment is a very difficult task that requires of a highly expertise training in order to achieve a good intraobserver and interobserver agreement. In this paper, we provide objective descriptors of the myocardium staining pattern by analyzing the spectrum of the image local statistics. The descriptors proposed discriminate among the different phenomena observed in the angiographic sequence and allow defining an objective score of the myocardial perfusion. |
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IAM;MILAB |
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IAM @ iam @ GRR2008 |
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1541 |
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