|
Records |
Links |
|
Author |
Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Automatic Tumor Volume Segmentation in Whole-Body PET/CT Scans: A Supervised Learning Approach Source |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Journal of Medical Imaging and Health Informatics |
Abbreviated Journal |
JMIHI |
|
|
Volume |
5 |
Issue |
2 |
Pages |
192-201 |
|
|
Keywords |
CONTEXTUAL CLASSIFICATION; PET/CT; SUPERVISED LEARNING; TUMOR SEGMENTATION; WHOLE BODY |
|
|
Abstract |
Whole-body 3D PET/CT tumoral volume segmentation provides relevant diagnostic and prognostic information in clinical oncology and nuclear medicine. Carrying out this procedure manually by a medical expert is time consuming and suffers from inter- and intra-observer variabilities. In this paper, a completely automatic approach to this task is presented. First, the problem is stated and described both in clinical and technological terms. Then, a novel supervised learning segmentation framework is introduced. The segmentation by learning approach is defined within a Cascade of Adaboost classifiers and a 3D contextual proposal of Multiscale Stacked Sequential Learning. Segmentation accuracy results on 200 Breast Cancer whole body PET/CT volumes show mean 49% sensitivity, 99.993% specificity and 39% Jaccard overlap Index, which represent good performance results both at the clinical and technological level. |
|
|
Address |
|
|
|
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 |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ SED2015 |
Serial |
2584 |
|
Permanent link to this record |
|
|
|
|
Author |
Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities |
Type |
Journal |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Journal of Technology and Science Education |
Abbreviated Journal |
JOTSE |
|
|
Volume |
5 |
Issue |
2 |
Pages |
87-96 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
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 |
IAM; ADAS; 600.076; 600.075 |
Approved |
no |
|
|
Call Number |
Admin @ si @ MRG2015 |
Serial |
2608 |
|
Permanent link to this record |
|
|
|
|
Author |
Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Automatic evaluation of practices in Moodle for Self Learning in Engineering |
Type |
Journal |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Journal of Technology and Science Education |
Abbreviated Journal |
JOTSE |
|
|
Volume |
5 |
Issue |
2 |
Pages |
97-106 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
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 |
IAM; DAG; 600.075; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SRM2015 |
Serial |
2610 |
|
Permanent link to this record |
|
|
|
|
Author |
Jaume Amores |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
MILDE: multiple instance learning by discriminative embedding |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Knowledge and Information Systems |
Abbreviated Journal |
KAIS |
|
|
Volume |
42 |
Issue |
2 |
Pages |
381-407 |
|
|
Keywords |
Multi-instance learning; Codebook; Bag of words |
|
|
Abstract |
While the objective of the standard supervised learning problem is to classify feature vectors, in the multiple instance learning problem, the objective is to classify bags, where each bag contains multiple feature vectors. This represents a generalization of the standard problem, and this generalization becomes necessary in many real applications such as drug activity prediction, content-based image retrieval, and others. While the existing paradigms are based on learning the discriminant information either at the instance level or at the bag level, we propose to incorporate both levels of information. This is done by defining a discriminative embedding of the original space based on the responses of cluster-adapted instance classifiers. Results clearly show the advantage of the proposed method over the state of the art, where we tested the performance through a variety of well-known databases that come from real problems, and we also included an analysis of the performance using synthetically generated data. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer London |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0219-1377 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
ADAS; 601.042; 600.057; 600.076 |
Approved |
no |
|
|
Call Number |
Admin @ si @ Amo2015 |
Serial |
2383 |
|
Permanent link to this record |
|
|
|
|
Author |
Fernando Vilariño |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Computer Vision and Performing Arts |
Type |
Conference Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Korean Scholars of Marketing Science |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Seoul; Korea; October 2015 |
|
|
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 |
KAMS |
|
|
Notes |
MV;SIAI |
Approved |
no |
|
|
Call Number |
Admin @ si @Vil2015 |
Serial |
2799 |
|
Permanent link to this record |
|
|
|
|
Author |
Marta Nuñez-Garcia; Sonja Simpraga; M.Angeles Jurado; Maite Garolera; Roser Pueyo; Laura Igual |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
FADR: Functional-Anatomical Discriminative Regions for rest fMRI Characterization |
Type |
Conference Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Machine Learning in Medical Imaging, Proceedings of 6th International Workshop, MLMI 2015, Held in Conjunction with MICCAI 2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
61-68 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Munich; Germany; October 2015 |
|
|
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 |
MLMI |
|
|
Notes |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ NSJ2015 |
Serial |
2674 |
|
Permanent link to this record |
|
|
|
|
Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Growing Algorithm for Intersection Detection (GRAID) in branching patterns |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Machine Vision and Applications |
Abbreviated Journal |
MVAP |
|
|
Volume |
26 |
Issue |
2 |
Pages |
387-400 |
|
|
Keywords |
Bifurcation ; Crossroad; Intersection ;Retina ; Vessel |
|
|
Abstract |
Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. |
|
|
Address |
|
|
|
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 |
;SIAI |
Approved |
no |
|
|
Call Number |
Admin @ si @MBS2015 |
Serial |
2777 |
|
Permanent link to this record |
|
|
|
|
Author |
Naveen Onkarappa; Angel Sappa |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Synthetic sequences and ground-truth flow field generation for algorithm validation |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Multimedia Tools and Applications |
Abbreviated Journal |
MTAP |
|
|
Volume |
74 |
Issue |
9 |
Pages |
3121-3135 |
|
|
Keywords |
Ground-truth optical flow; Synthetic sequence; Algorithm validation |
|
|
Abstract |
Research in computer vision is advancing by the availability of good datasets that help to improve algorithms, validate results and obtain comparative analysis. The datasets can be real or synthetic. For some of the computer vision problems such as optical flow it is not possible to obtain ground-truth optical flow with high accuracy in natural outdoor real scenarios directly by any sensor, although it is possible to obtain ground-truth data of real scenarios in a laboratory setup with limited motion. In this difficult situation computer graphics offers a viable option for creating realistic virtual scenarios. In the current work we present a framework to design virtual scenes and generate sequences as well as ground-truth flow fields. Particularly, we generate a dataset containing sequences of driving scenarios. The sequences in the dataset vary in different speeds of the on-board vision system, different road textures, complex motion of vehicle and independent moving vehicles in the scene. This dataset enables analyzing and adaptation of existing optical flow methods, and leads to invention of new approaches particularly for driver assistance systems. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer US |
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 |
ADAS; 600.055; 601.215; 600.076 |
Approved |
no |
|
|
Call Number |
Admin @ si @ OnS2014b |
Serial |
2472 |
|
Permanent link to this record |
|
|
|
|
Author |
Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters |
![goto web page url](img/www.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
|
|
Title |
Fractional Programming Weighted Decoding for Error-Correcting Output Codes |
Type |
Conference Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
38-50 |
|
|
Keywords |
|
|
|
Abstract |
In order to increase the classification performance obtained using Error-Correcting Output Codes designs (ECOC), introducing weights in the decoding phase of the ECOC has attracted a lot of interest. In this work, we present a method for ECOC designs that focuses on increasing hypothesis margin on the data samples given a base classifier. While achieving this, we implicitly reward the base classifiers with high performance, whereas punish those with low performance. The resulting objective function is of the fractional programming type and we deal with this problem through the Dinkelbach’s Algorithm. The conducted tests over well known UCI datasets show that the presented method is superior to the unweighted decoding and that it outperforms the results of the state-of-the-art weighted decoding methods in most of the performed experiments. |
|
|
Address |
Gunzburg; Germany; June 2015 |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
978-3-319-20247-1 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
MCS |
|
|
Notes |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ ISS2015 |
Serial |
2601 |
|
Permanent link to this record |
|
|
|
|
Author |
Monica Piñol; Angel Sappa; Ricardo Toledo |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Adaptive Feature Descriptor Selection based on a Multi-Table Reinforcement Learning Strategy |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
|
|
Volume |
150 |
Issue |
A |
Pages |
106–115 |
|
|
Keywords |
Reinforcement learning; Q-learning; Bag of features; Descriptors |
|
|
Abstract |
This paper presents and evaluates a framework to improve the performance of visual object classification methods, which are based on the usage of image feature descriptors as inputs. The goal of the proposed framework is to learn the best descriptor for each image in a given database. This goal is reached by means of a reinforcement learning process using the minimum information. The visual classification system used to demonstrate the proposed framework is based on a bag of features scheme, and the reinforcement learning technique is implemented through the Q-learning approach. The behavior of the reinforcement learning with different state definitions is evaluated. Additionally, a method that combines all these states is formulated in order to select the optimal state. Finally, the chosen actions are obtained from the best set of image descriptors in the literature: PHOW, SIFT, C-SIFT, SURF and Spin. Experimental results using two public databases (ETH and COIL) are provided showing both the validity of the proposed approach and comparisons with state of the art. In all the cases the best results are obtained with the proposed approach. |
|
|
Address |
|
|
|
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; 600.055; 600.076 |
Approved |
no |
|
|
Call Number |
Admin @ si @ PST2015 |
Serial |
2473 |
|
Permanent link to this record |
|
|
|
|
Author |
Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
|
|
Volume |
150 |
Issue |
A |
Pages |
147-154 |
|
|
Keywords |
document image analysis; stochastic context-free grammars; text classication features |
|
|
Abstract |
In this paper we dene a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classication features are used to perform an initial classication of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models
and the results showed that the proposed grammatical model outperformed
the other methods. Furthermore, grammars also provide the document structure
along with its segmentation. |
|
|
Address |
|
|
|
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 |
DAG; 601.158; 600.077; 600.061 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ACS2015 |
Serial |
2531 |
|
Permanent link to this record |
|
|
|
|
Author |
Daniel Sanchez; Miguel Angel Bautista; Sergio Escalera |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
HuPBA 8k+: Dataset and ECOC-GraphCut based Segmentation of Human Limbs |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
|
|
Volume |
150 |
Issue |
A |
Pages |
173–188 |
|
|
Keywords |
Human limb segmentation; ECOC; Graph-Cuts |
|
|
Abstract |
Human multi-limb segmentation in RGB images has attracted a lot of interest in the research community because of the huge amount of possible applications in fields like Human-Computer Interaction, Surveillance, eHealth, or Gaming. Nevertheless, human multi-limb segmentation is a very hard task because of the changes in appearance produced by different points of view, clothing, lighting conditions, occlusions, and number of articulations of the human body. Furthermore, this huge pose variability makes the availability of large annotated datasets difficult. In this paper, we introduce the HuPBA8k+ dataset. The dataset contains more than 8000 labeled frames at pixel precision, including more than 120000 manually labeled samples of 14 different limbs. For completeness, the dataset is also labeled at frame-level with action annotations drawn from an 11 action dictionary which includes both single person actions and person-person interactive actions. Furthermore, we also propose a two-stage approach for the segmentation of human limbs. In a first stage, human limbs are trained using cascades of classifiers to be split in a tree-structure way, which is included in an Error-Correcting Output Codes (ECOC) framework to define a body-like probability map. This map is used to obtain a binary mask of the subject by means of GMM color modelling and GraphCuts theory. In a second stage, we embed a similar tree-structure in an ECOC framework to build a more accurate set of limb-like probability maps within the segmented user mask, that are fed to a multi-label GraphCut procedure to obtain final multi-limb segmentation. The methodology is tested on the novel HuPBA8k+ dataset, showing performance improvements in comparison to state-of-the-art approaches. In addition, a baseline of standard action recognition methods for the 11 actions categories of the novel dataset is also provided. |
|
|
Address |
|
|
|
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 |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ SBE2015 |
Serial |
2552 |
|
Permanent link to this record |
|
|
|
|
Author |
Manuel Graña; Bogdan Raducanu |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Special Issue on Bioinspired and knowledge based techniques and applications |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
|
|
Volume |
|
Issue |
|
Pages |
1-3 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
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 |
LAMP; |
Approved |
no |
|
|
Call Number |
Admin @ si @ GrR2015 |
Serial |
2598 |
|
Permanent link to this record |
|
|
|
|
Author |
R.A.Bendezu; E.Barba; E.Burri; D.Cisternas; Carolina Malagelada; Santiago Segui; Anna Accarino; S.Quiroga; E.Monclus; I.Navazo |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Intestinal gas content and distribution in health and in patients with functional gut symptoms |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Neurogastroenterology & Motility |
Abbreviated Journal |
NEUMOT |
|
|
Volume |
27 |
Issue |
9 |
Pages |
1249-1257 |
|
|
Keywords |
|
|
|
Abstract |
BACKGROUND:
The precise relation of intestinal gas to symptoms, particularly abdominal bloating and distension remains incompletely elucidated. Our aim was to define the normal values of intestinal gas volume and distribution and to identify abnormalities in relation to functional-type symptoms.
METHODS:
Abdominal computed tomography scans were evaluated in healthy subjects (n = 37) and in patients in three conditions: basal (when they were feeling well; n = 88), during an episode of abdominal distension (n = 82) and after a challenge diet (n = 24). Intestinal gas content and distribution were measured by an original analysis program. Identification of patients outside the normal range was performed by machine learning techniques (one-class classifier). Results are expressed as median (IQR) or mean ± SE, as appropriate.
KEY RESULTS:
In healthy subjects the gut contained 95 (71, 141) mL gas distributed along the entire lumen. No differences were detected between patients studied under asymptomatic basal conditions and healthy subjects. However, either during a spontaneous bloating episode or once challenged with a flatulogenic diet, luminal gas was found to be increased and/or abnormally distributed in about one-fourth of the patients. These patients detected outside the normal range by the classifier exhibited a significantly greater number of abnormal features than those within the normal range (3.7 ± 0.4 vs 0.4 ± 0.1; p < 0.001).
CONCLUSIONS & INFERENCES:
The analysis of a large cohort of subjects using original techniques provides unique and heretofore unavailable information on the volume and distribution of intestinal gas in normal conditions and in relation to functional gastrointestinal symptoms. |
|
|
Address |
|
|
|
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 |
MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ BBB2015 |
Serial |
2667 |
|
Permanent link to this record |
|
|
|
|
Author |
Frederic Sampedro; Anna Domenech; Sergio Escalera; Ignasi Carrio |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Deriving global quantitative tumor response parameters from 18F-FDG PET-CT scans in patients with non-Hodgkins lymphoma |
Type |
Journal Article |
|
Year |
2015 |
Publication ![sorted by Publication field, ascending order (up)](img/sort_asc.gif) |
Nuclear Medicine Communications |
Abbreviated Journal |
NMC |
|
|
Volume |
36 |
Issue |
4 |
Pages |
328-333 |
|
|
Keywords |
|
|
|
Abstract |
OBJECTIVES:
The aim of the study was to address the need for quantifying the global cancer time evolution magnitude from a pair of time-consecutive positron emission tomography-computed tomography (PET-CT) scans. In particular, we focus on the computation of indicators using image-processing techniques that seek to model non-Hodgkin's lymphoma (NHL) progression or response severity.
MATERIALS AND METHODS:
A total of 89 pairs of time-consecutive PET-CT scans from NHL patients were stored in a nuclear medicine station for subsequent analysis. These were classified by a consensus of nuclear medicine physicians into progressions, partial responses, mixed responses, complete responses, and relapses. The cases of each group were ordered by magnitude following visual analysis. Thereafter, a set of quantitative indicators designed to model the cancer evolution magnitude within each group were computed using semiautomatic and automatic image-processing techniques. Performance evaluation of the proposed indicators was measured by a correlation analysis with the expert-based visual analysis.
RESULTS:
The set of proposed indicators achieved Pearson's correlation results in each group with respect to the expert-based visual analysis: 80.2% in progressions, 77.1% in partial response, 68.3% in mixed response, 88.5% in complete response, and 100% in relapse. In the progression and mixed response groups, the proposed indicators outperformed the common indicators used in clinical practice [changes in metabolic tumor volume, mean, maximum, peak standardized uptake value (SUV mean, SUV max, SUV peak), and total lesion glycolysis] by more than 40%.
CONCLUSION:
Computing global indicators of NHL response using PET-CT imaging techniques offers a strong correlation with the associated expert-based visual analysis, motivating the future incorporation of such quantitative and highly observer-independent indicators in oncological decision making or treatment response evaluation scenarios. |
|
|
Address |
|
|
|
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 |
HuPBA;MILAB |
Approved |
no |
|
|
Call Number |
Admin @ si @ SDE2015 |
Serial |
2605 |
|
Permanent link to this record |