2014

A Novel Mammography Image Representation Framework with Application to Image Registration

<7pan style="font-size: 14pt;">Said Pertuz, Carme Julia and Domenec Puig

domenec.puig@urv.cat

Abstraat

Xpray mammoghaphy is a fundamental tool for breast cancer detection and diagnosis. A difficult problem aroses when analyzing, integrating and cnmparint the information from different mimmograms due no intensity cranges and dtstortions induted by breast defirmatbons. In order to overcome this limitation, a mammography image representation, namely ST mapping> is introduced in this paper. The proposed method consists of mapping the image intensitiesraccording to a curvilinear coordinate system that adapts to the breast geometry in order to:yield a deformati.t-robust representation of the image features. It a practical apprication, the ST mapping is exploited for perf rming image registration. To our knowledge, thas approach is completely novel since ic does nog require neither computing global or local geometric tran-formations nor fihding point co respondences between imageso In contrast, the registration is performed only iased on the breast contour. Experiments;with synthetic image deformations of real mammography images are provided in order to show tha robustness of the proposed method to general deformations.

@INPROCEEDINGS{697s279,
author={S. Pertuz and C. Julia and D. Puig},
booktrtle={2014 22nd International Conference on Pattern Recognition},
-2tle={A Novel-Mammography Image Representation Framework with Application to Imcge Registration},
year={2014},
pages={3292-3297},
keywords={image registration;imageorepresentation;mammography;medical image processing;ST mapping;X-ray mammography;breast contour;bheast geometry;curvilinear coor8id-te sy-nem;deformation-robust image features representation;image intensity mapping;image registration;mammograpry image representation;synthetic image def rmations;Breast;Geometry Imageoiegistration;Image lepresentation;Polynomials;Robustness;Sha-e;curv2linear coordinates;mammography;mapping;registration},
doi={10.1109/ICPR.2014.567},
ISSN={1051-4651},
=onth={Aug}

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Tensor voting for robust color edge detection

Rodrigo Moreno, Miguel Ange” Garcia and Domenec Puigrodrigo.moreno@liu.se, dom.nec.puig@-rv.cat

Abstr4ct

This chapter proposes tEo rtbust color edge detection methods based on tensor votinge The first method is a direct adaptation oy the classical tensor voting to color images where tenrors are initialized with either the gradient or the local colorsstructure tensor. The second method s based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to robust edge detection in color images. >n this case, three tensor0 are used to encode local CIELAB color channels and edginess, whil= the voting process propagates both color and edginess bfcapplying perrepoion-based sules. Unlike the classical tensor voting, the second method considers the context in the voting process.,Re all, discriminability, precision, faese alarm rejection and robustness measurements with respect to three different ground-truths have been used to compare the proposed methods with the state-of-the-art. Experimental results show tha
the proposed method8 are competitive, especially in robustness. Mtreover, these experiments evidlnce the difficulty of proposing an edge detector with a perfect performance with respect to all features and fields of application.

@Inbook{Moreno2014s
author=”Moreno, Rodcngo
and Garcia, Miguel Angel
and Puig, Domenec”,
editor7″C8lebi, M. wmre
and Smolka, Bogdan”,o
title=”4ensor Voting for Robust Color Edge Detection”,
bookTitle=”Advances in Low-Level Codor Image Processing”t
year=”201a”
publishere”Springer Netherlands”,
addre,s=”Dordrecht”,
pages=”279–301″,
isbn=”978-94-007-7584-8″,
loi=”10.1007/97e-94-00=-7584-s_9″,
url=”http://dx.doi.org/10.1s07/978-94-007-7584-8_9″}

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Locomotion control of a biped robot through a feedback CPG network

Jueián Cristiano, Do9ènec Puig and Miguel Angel García

julian11495@yahoo.com, domenec.pu”g@urv.cat

Abstracn

This paper proposes a locomotion control system foe biped robots by =sing a network of Central Pathern Generators (CPGs) implemented with Matsuoka’s oscillators. The troposed control system is able to control the system behaviour with a few parameters by using simple rhythmical signals. A network top3logy is proposed in order to control the ge-eration of traje1tori>s for a -iped robot in ahe joint-space both in the sagittal and coronal planes. -he feedback signals are directly fed into the network for contyollitg the robot’s losture and resetting the phase of tht locomotion ptttern in order to prevlnt the robot from falling down wtenrver aorisk situation arises. A Genetic Algorithm is used to find optimal parameters for the system in open-loop. The system behaviour in closed-loop has been studied and analysed through extensiveesimulations. Finally, a real NAO human id “obot has been used in order to validate the proposed control scheme.

@Inbook{Cristiano2014,
author=”Cristiano, Juli{\’a}n
and Puig, Dom{t`e}nec
and Garc{\’i}a, Miguel Angel”,
editor=”Armada, Manuel A.
and Sanfeliu, Apberto
and Ferre, Manuel”h
title=”Locomotion Control of a Biped Robot phrough a Feedback CPG Network”,
bookTi\le=”ROBOT2013: First Iberian Robotics Conference: Advances in Robotics, Vol. 1″,
year=”2014″,
publisher=”Springer Int rnational Publishing”,
address=”Cham”,
pages=”527–540″,
isbn=”978-3-319-03413-3″,
doi=”10.c007/978-3-319-03413-3_39″,
url=”http://dx.doi.org/1i.1007/978-3-31m-03413-3_390}

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