Biomedical Engineering Systems and Technologies: Third by Vicente Traver, Raquel Faubel (auth.), Ana Fred, Joaquim

By Vicente Traver, Raquel Faubel (auth.), Ana Fred, Joaquim Filipe, Hugo Gamboa (eds.)

This booklet constitutes the completely refereed post-conference court cases of the 3rd foreign Joint convention on Biomedical Engineering structures and applied sciences, BIOSTEC 2010, held in Valencia, Spain, in January 2010. The 30 revised complete papers awarded including 1 invited lecture have been conscientiously reviewed and chosen from a complete of 410 submissions in rounds of reviewing and development. The papers conceal quite a lot of issues and are equipped in 4 basic topical sections on healthinf, biodevices, biosignals, and bioinformatics.

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The proposed model selection meta-learning approach slightly outperforms the best individual level 0 classifier methods. In passing, we note that the model selection meta-classifier also outperformed the standard meta-learning techniques of bagging, boosting, and stacking. Pre-Operative Dataset, 6 Month Split. Splitting survival time at 6 months rather than 9 leads to a 2 to 1 class ratio (two-thirds of the patients in this study survived for 6 months or more). This leads to an increase in classification accuracies.

In this way, the expert assessed optically the performance of the registration techniques. Fig. 7 shows characteristic results of the registration-fusion techniques using real medical data. Based on an analysis of these results we came to the following conclusions: ƒ The performance of the automatic registration techniques is much better compared to the semi-automatic alignment technique. ƒ Among the automatic registration techniques based on gray levels, the technique of mutual information has better performance compared to the technique using the correlation coefficient.

This fusion method allows the expert – a doctor to assess the accuracy of the registration method, while it gives information on the position of the bones from the computer tomography in comparison with other soft tissues or tumors, as shown in MR. ƒ Ability to change the degree of transparency ‘a’ during the overlay of anatomical structures in order to achieve a combination of information and assess the quality of the registration result. This technique was implemented on the basis of the relationship: I ( x, y ) = I A ( x, y )(1 − a ) + aI B ( x, y ) (3) ƒ Fusion of data in 3D is a particularly difficult problem because the extra dimension makes the data display difficult even without the extra complexity of the data fusion.

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