Abstract book (pdf) - ICPR 2010

cally presented simultaneously. Twenty participants were recruited to distinguish and gave different reactions to these two
types of stimuli. The neural activations caused by their reactions were recorded by MEG system and 3T magnetic DTI
scanner. Virtual sensor technique and wavelet beam former source analysis, which were state-of-the-art methods, were
used to study the MEG and DTI data. Three responses were evoked in the MEG waveform and M160 was identified in
the left temporal-occipital junction. All the results coincided with the previous studies’ conclusions, which indicated that
the integration of virtual sensor and wavelet beam former were effective techniques in analyzing the MEG and DTI data.
09:00-11:10, Paper WeAT9.10
A Hypothesis Testing Approach for Fluorescent Blob Identification
Wu, Le-Shin, Indiana Univ.
Shaw, Sidney, Indiana Univ.
Template matching is a common approach for identifying fluorescent objects within a biological image. But how to decide
a threshold value for the purpose of justifying the goodness of matching score is a rather difficult task. In this paper, we
propose a framework that dynamically chooses appropriate threshold values for correct object identification at a non-arbitrary
statistical power based on the local measure of signal and noise. We validate the feasibility of our proposed framework
by presenting simulation experiments conducted with both synthetic and live-cell data sets. The experimental results
suggest that our auto-thresholding algorithm and local signal to noise ratio estimation can provide solid means for effective
spot identity in place of an ad hoc threshold fitting value or minimization method.
09:00-11:10, Paper WeAT9.11
Automated Detection of Nucleoplasmic Bridges for DNA Damage Scoring in Binucleated Cells
Sun, Changming, CSIRO
Vallotton, Pascal, CSIRO
Fenech, Michael, CSIRO
Thomas, Phil, CSIRO
Quantification of DNA damage, which may be caused by radiation or exposure to chemicals, is very important and can be
very time consuming and subject to variability if carried out visually. The quantification of scoring DNA damage includes
biomarkers such as micronuclei, nucleoplasmic bridges, and nuclear buds as scored in cytokinesis-blocked binucleated
cells. In this paper, we present a new algorithm based on a shortest path technique that enables us to detect the nucleoplasmic
bridges joining two nuclei in cell images of binucleated cells. The effectiveness of our algorithm is illustrated using
a set of cell images. We believe that this is the first time that a feasible automated nucleoplasmic bridge detection system
has been reported.
09:00-11:10, Paper WeAT9.12
Multiple Model Estimation for the Detection of Curvilinear Segments in Medical X-Ray Images using Sparse-Plus-
Dense-RANSAC
Papalazarou, Chrysi, Eindhoven Univ. of Tech.
De With, Peter H. N., Eindhoven Univ. of Tech. / CycloMedia
Rongen, Peter, Philips Healthcare
In this paper, we build on the RANSAC method to detect multiple instances of objects in an image, where the objects are
modeled as curvilinear segments with distinct endpoints. Our approach differs from previously presented work in that it
incorporates soft constraints, based on a dense image representation, that guide the estimation process in every step. This
enables (1) better correspondence with image content, (2) explicit endpoint detection and (3) a reduction in the number of
iterations required for accurate estimation. In the case of curvilinear objects examined in this paper, these constraints are
formulated as binary image labels, where the estimation proved to be robust to mislabeling, e.g. in case of intersections.
Results for both synthetic and real data from medical X-ray images show the improvement from incorporating soft imagebased
constraints.
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