Download e-book for kindle: Bio-Imaging and Visualization for Patient-Customized by Huafeng Wang, Lihong Li, Hao Han (auth.), João Manuel R. S.

By Huafeng Wang, Lihong Li, Hao Han (auth.), João Manuel R. S. Tavares, Xiongbiao Luo, Shuo Li (eds.)

ISBN-10: 3319035894

ISBN-13: 9783319035895

ISBN-10: 3319035908

ISBN-13: 9783319035901

This ebook includes the complete papers awarded on the MICCAI 2013 workshop Bio-Imaging and Visualization for Patient-Customized Simulations (MWBIVPCS 2013). MWBIVPCS 2013 introduced jointly researchers representing a number of fields, corresponding to Biomechanics, Engineering, drugs, arithmetic, Physics and Statistic.

The contributions integrated during this booklet current and speak about new traits in these fields, utilizing a number of tools and strategies, together with the finite aspect strategy, similarity metrics, optimization approaches, graphs, hidden Markov versions, sensor calibration, fuzzy good judgment, facts mining, mobile automation, lively form versions, template matching and point units. those function instruments to handle extra successfully diverse and well timed functions concerning sign and snapshot acquisition, snapshot processing and research, picture segmentation, snapshot registration and fusion, desktop simulation, photograph established modelling, simulation and surgical making plans, picture guided robotic assisted surgical and photograph established diagnosis.

This booklet will entice researchers, PhD scholars and graduate scholars with multidisciplinary pursuits regarding the parts of clinical imaging, photo processing and research, desktop imaginative and prescient, photo segmentation, photo registration and fusion, medical facts visualization and photo dependent modeling and simulation.

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In: International conference on computer vision theory and applications 28 F. Li and F. Porikli 14. Santhanam A, Fidopiastis C, Hamza-Lup F, Rolland J, Imielinska C (2004) Physically-based deformation of high-resolution 3d lung models for augmented reality based medical visualization. In: Medical image computing and computer aided intervention, AMI-ARCS, pp 21–32 15. Segars W, Lalush D, Tsui B (2001) Modeling respiratory mechanics in the MCAT and splinebased MCAT phantoms. IEEE Trans Nucl Sci 48(1):89–97 16.

E Specificity and Precision. f Accuracy. g FOM. h MER. i Ih A Graph Based Methodology for Volumetric Left Ventricle Segmentation (a) (b) (c) (d) (e) (f) (g) (h) (i) (j) (k) (l) 49 Fig. 2 a–c Original images. d–f Ground truth images. g–i Segmented images due to CA. j–l Segmented images due to DCA 50 S. P. Dakua et al. truth images have been provided along with the datasets by the respective organizations. While evaluating the performance, we first examine the performance of conventional CA which is ruminated in Fig.

45 s. More details about SWF and volume rendering techniques can be found in [1–5, 9, 10]. 2 Similarity Measure In our framework, two novel image similarity measures are adopted from [11] and [12]. The first one is called exponential correlation (EC). The other is called pixelbased individual entropy correlation coefficient (IECC). Both are used as the similarity measure between the DRR images and the reference X-ray image in order to evaluate the current quality of alignment. ] denotes the expectation operator over the D X .

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Bio-Imaging and Visualization for Patient-Customized Simulations by Huafeng Wang, Lihong Li, Hao Han (auth.), João Manuel R. S. Tavares, Xiongbiao Luo, Shuo Li (eds.)


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