By M. Jorge Cardoso, Ivor Simpson, Tal Arbel, Doina Precup, Annemie Ribbens
This e-book constitutes the refereed complaints of the 1st foreign Workshop on Bayesian and grAphical versions for Biomedical Imaging, BAMBI 2014, held in Cambridge, MA, united states, in September 2014 as a satellite tv for pc occasion of the seventeenth overseas convention on clinical picture Computing and machine Assisted Intervention, MICCAI 2014.
The eleven revised complete papers offered have been rigorously reviewed and chosen from various submissions with a key point on probabilistic modeling utilized to scientific photo research. The goals of this workshop in comparison to different workshops, e.g. laptop studying in scientific imaging, have a more robust mathematical specialise in the rules of probabilistic modeling and inference. The papers spotlight the possibility of utilizing Bayesian or random box graphical types for advancing medical learn in biomedical photograph research or for the development of modeling and research of scientific imaging data.
Read or Download Bayesian and grAphical Models for Biomedical Imaging: First International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers PDF
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Extra info for Bayesian and grAphical Models for Biomedical Imaging: First International Workshop, BAMBI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers
So far, relatively generic prior knowledge on cell movement and proliferation has been encoded into assignment models: Cells can be kept from moving too far between time frames; They can be allowed to divide but not merge; They can be kept from dividing into more than two, and kept from appearing from nowhere. However, none of the previously published assignment models captures a particular kind of prior knowledge that is important for cells in the Mother Machine, namely the total order of cells within growth channels which has to be maintained at any time.
Experiments are imaged by an inverted microscope equipped with an incubator. Images are taken every minute using a 100x objective. Raw data from the microscope undergoes a few simple preprocessing steps. Two of those are of particular importance. First, movie frames are rotated into an upright orientation, because growth channels are usually tilted by up to ±45◦ , see Figure 1(b). To determine the tilt angle, we smooth each image row, collect local maxima, and ﬁt straight lines through each growth channel.
Comparison of the two JDE versions on real data in the auditory and visual cortex.