Milagros Martinez

Dr. Milagros Martinez

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Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 August 2004 in Robotics and Autonomous Systems
Verified
Journal Article
Closed access
GBGines Benet
Gines Benet
MMMilagros Martinez
Milagros Martinez
Francisco NogueraFrancisco Noguera
Francisco Noguera
PPPascual Pérez
Pascual Pérez
José SimóJosé Simó
José Simó

30 November 2010 in Sensors
Verified
Journal Article
Open access
PDF file
MMMilagros Martinez
Milagros Martinez
GBGines Benet
Gines Benet
Ultrasonic signals coming from rotary sonar sensors in a robot gives us several features about the environment. This enables us to locate and classify the objects in the scenario of the robot. Each object and reflector produces a series of peaks in the amplitude of the signal. The radial and angular position of the sonar sensor gives information about location and their amplitudes offer information about the nature of the surface. Early works showed that the amplitude can be modeled and used to classify objects with very good results at short distances—80% average success in classifying both walls and corners at distances less than 1.5 m. In this paper, a new set of geometric features derived from the amplitude analysis of the echo is presented. These features constitute a set of characteristics that can be used to improve the results of classification at distances from 1.5 m to 4 m. Also, a comparative study on classification algorithms widely used in pattern recognition techniques has been carried out for sensor distances ranging between 0.5 to 4 m, and with incidence angles ranging between 20º to 70º. Experimental results show an enhancement on the success in classification rates when these geometric features are considered.

27 September 2016 in Entropy
Verified
Journal Article
Open access
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MMMilagros Martinez
Milagros Martinez
RMRafa Martinez
Rafa Martinez
Luis Manuel Sánchez RuizLuis Manuel Sánchez Ruiz
Luis Manuel Sánchez Ruiz
Peris Fajarnes GuillermoPeris Fajarnes Guillermo
Peris Fajarnes Guillermo
Whole-body 123I-Metaiodobenzylguanidine (mIBG) scintigraphy is used as primary image modality to visualize neuroblastoma tumours and metastases because it is the most sensitive and specific radioactive tracer in staging the disease and evaluating the response to treatment. However, especially in paediatric neuroblastoma, information from mIBG scans is difficult to extract because of acquisition difficulties that produce low definition images, with poor contours, resolution and contrast. These problems limit physician assessment. Current oncological guidelines are based on qualitative observer-dependant analysis. This makes comparing results taken at different moments of therapy, or in different institutions, difficult. In this paper, we present a computerized method that processes an image and calculates a quantitative measurement considered as its entropy, suitable for the identification of abnormal uptake regions, for which there is enough suspicion that they may be a tumour or metastatic site. This measurement can also be compared with future scintigraphies of the same patient. Over 46 scintigraphies of 22 anonymous patients were tested; the procedure identified 96.7% of regions of abnormal uptake and it showed a low overall false negative rate of 3.3%. This method provides assistance to physicians in diagnosing tumours and also allows the monitoring of patients’ evolution.