Information Processing in Medical Imaging: 24th - download pdf or read online

By Sebastien Ourselin, Daniel C. Alexander, Carl-Fredrik Westin, M. Jorge Cardoso

ISBN-10: 3319199919

ISBN-13: 9783319199917

ISBN-10: 3319199927

ISBN-13: 9783319199924

This booklet constitutes the court cases of the twenty fourth overseas convention on info Processing in scientific Imaging, IPMI 2015, held on the Sabhal Mor Ostaig collage at the Isle of Skye, Scotland, united kingdom, in June/July 2015.

The 22 complete papers and forty-one poster papers awarded during this quantity have been rigorously reviewed and chosen from 195 submissions. They have been geared up in topical sections named: probabilistic graphical versions; MRI reconstruction; clustering; statistical tools; longitudinal research; microstructure imaging; form research; multi-atlas fusion; quickly photo registration; deformation types; and the poster session.

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Extra info for Information Processing in Medical Imaging: 24th International Conference, IPMI 2015, Sabhal Mor Ostaig, Isle of Skye, UK, June 28 - July 3, 2015, Proceedings

Example text

In this work, given N previously observed images, the inlier model is defined as a mixture model given by p(˜ yi , x ˜i , j|liI , X , θ) = 1 N N p(˜ yi , x ˜i |liI , jn , Xn , θ)p(jn |liI , θ). , the probability of observing a certain pair of intensities {˜ yi , x weighted mixture of the N probabilities of observing the pair given a previously observed pair Xn . J. Cardoso et al. As in the Non-Local STAPLE algorithm [6], we assume that jn is unknown, or at least uncertain, as the coordinate mapping problem is ill posed [7].

0 3. 5 4. 0 4. 5 5. 0 (4,2) (8,4) (9,5) (13,5) (12,6) (10,8) (12,6) (13,7) (11,7) (13,8) ω Fig. 2. Simulated data results. Left: variational lower bound F (q ∗ ) for different values of (α, ω). Middle: the number of topics discovered by the model as a function of ω averaged over α. Right: normalized mutual information between the true and the discovered topics for our method and for k-means clustering (K-M) applied to pooled data. The number of discovered topics is reported in brackets under the corresponding value of ω (w gene, w/o gene).

On the other side, y |X , θ)] and [3]. no significant different was found between the expectation Ey˜[p(˜ Furthermore, to test the presence of bias in the synthesis process we also esti1 mated the mean error (ME), defined as ME = |Ω| i (pseudoCTi − realCTi ). 5) HU and did not significantly differ from zero, supporting the idea that the current synthesis approach is unbiased. 2 Quantitative Assessment of the Outlier Segmentation Using Brainweb The 3 multiple sclerosis (MS) datasets (mild, moderate and severe models) and one normal anatomy dataset were generated using the BrainWeb MR image simulator.

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Information Processing in Medical Imaging: 24th International Conference, IPMI 2015, Sabhal Mor Ostaig, Isle of Skye, UK, June 28 - July 3, 2015, Proceedings by Sebastien Ourselin, Daniel C. Alexander, Carl-Fredrik Westin, M. Jorge Cardoso


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