toggle visibility Search & Display Options
Select All    Deselect All << 1 2 3 4 5 6 7 8 9 10 >> [11–20]
List View
 | 
Citations
 | 
Details
  Records Links
Author Rozenn Dhayot; Fernando Vilariño; Gerard Lacey edit  doi
openurl 
  Title Improving the Quality of Color Colonoscopy Videos Type Journal Article
  Year 2008 Publication EURASIP Journal on Image and Video Processing Abbreviated Journal EURASIP JIVP  
  Volume 139429 Issue 1 Pages (up) 1-9  
  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 800 Expedition Conference  
  Notes MV;SIAI Approved no  
  Call Number fernando @ fernando @ Serial 2422  
Permanent link to this record
 
 
Author Manuel Graña; Bogdan Raducanu edit  doi
openurl 
  Title Special Issue on Bioinspired and knowledge based techniques and applications Type Journal Article
  Year 2015 Publication Neurocomputing Abbreviated Journal NEUCOM  
  Volume Issue Pages (up) 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;;MV Approved no  
  Call Number Admin @ si @ GrR2015 Serial 2598  
Permanent link to this record
 
 
Author F. Javier Sanchez; Jorge Bernal; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach edit   pdf
url  openurl
  Title Bright spot regions segmentation and classification for specular highlights detection in colonoscopy videos Type Journal Article
  Year 2017 Publication Machine Vision and Applications Abbreviated Journal MVAP  
  Volume Issue Pages (up) 1-20  
  Keywords Specular highlights; bright spot regions segmentation; region classification; colonoscopy  
  Abstract A novel specular highlights detection method in colonoscopy videos is presented. The method is based on a model of appearance dening specular
highlights as bright spots which are highly contrasted with respect to adjacent regions. Our approach proposes two stages; segmentation, and then classication
of bright spot regions. The former denes a set of candidate regions obtained through a region growing process with local maxima as initial region seeds. This process creates a tree structure which keeps track, at each growing iteration, of the region frontier contrast; nal regions provided depend on restrictions over contrast value. Non-specular regions are ltered through a classication stage performed by a linear SVM classier using model-based features from each region. We introduce a new validation database with more than 25; 000 regions along with their corresponding pixel-wise annotations. We perform a comparative study against other approaches. Results show that our method is superior to other approaches, with our segmented regions being
closer to actual specular regions in the image. Finally, we also present how our methodology can also be used to obtain an accurate prediction of polyp histology.		  
  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 MV; 600.096; 600.175 Approved no  
  Call Number Admin @ si @ SBS2017 Serial 2975  
Permanent link to this record
 
 
Author Carola Figueroa Flores; David Berga; Joost Van de Weijer; Bogdan Raducanu edit   pdf
url  openurl
  Title Saliency for free: Saliency prediction as a side-effect of object recognition Type Journal Article
  Year 2021 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 150 Issue Pages (up) 1-7  
  Keywords Saliency maps; Unsupervised learning; Object recognition  
  Abstract Saliency is the perceptual capacity of our visual system to focus our attention (i.e. gaze) on relevant objects instead of the background. So far, computational methods for saliency estimation required the explicit generation of a saliency map, process which is usually achieved via eyetracking experiments on still images. This is a tedious process that needs to be repeated for each new dataset. In the current paper, we demonstrate that is possible to automatically generate saliency maps without ground-truth. In our approach, saliency maps are learned as a side effect of object recognition. Extensive experiments carried out on both real and synthetic datasets demonstrated that our approach is able to generate accurate saliency maps, achieving competitive results when compared with supervised methods.  
  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; 600.147; 600.120;MV Approved no  
  Call Number Admin @ si @ FBW2021 Serial 3559  
Permanent link to this record
 
 
Author Jorge Bernal edit   pdf
url  openurl
  Title Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps Type Journal Article
  Year 2014 Publication Electronic Letters on Computer Vision and Image Analysis Abbreviated Journal ELCVIA  
  Volume 13 Issue 2 Pages (up) 9-10  
  Keywords Colonoscopy; polyp localization; polyp segmentation; Eye-tracking  
  Abstract Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Alicia Fornes; Volkmar Frinken  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MV Approved no  
  Call Number Admin @ si @ Ber2014 Serial 2487  
Permanent link to this record
Select All    Deselect All << 1 2 3 4 5 6 7 8 9 10 >> [11–20]
List View
 | 
Citations
 | 
Details
toggle visibility
Save Citations:
Export Records: