This paper reports on a method to distinguish true from false of the loop in the blood vessel graph. Most conventional
studies have used a graph to represent 3D blood vessels structure. Blood vessels graph sometimes has a false loop and
this exerts a harmful influence to the graph analysis. Conventional study simply cut them but this is not suitable for the
graph include real loop. For this reason, we try to distinguish true from false of the loop in the graph. Our method uses
the loop inside and the outside main blood vessel shape to distinguish the similar loop. This main blood vessel we called
route is long, thick, and not shares to other route as much as possible. Even if a graph includes false loop, this main route
will avoid the false connection and detect the same main blood vessel. Our method detects such a main route in each loop branch point and stores it as the outside feature for comparing. Inside feature is measured by converting the inside blood vessels as one route. Each loop is compared by the graph edit distance. Graph edit distance is easily able to deal with the route adding, deleting and replacing. Our method was tested by the cerebral blood vessels image in MRI. Our method tried to detect the arterial cycles of Willis from the graph including false loops. As a result, our method detected it correctly in four data from five.
In the field of biology, compensation of multiple fluorescence is necessary for quantitative measurement of samples.
Conventional methods depend on a linear combination model irrespective of the model's adequacy. Therefore,
proper compensation has not been performed in some situations. To overcome this problem, we propose a
method for performing nonlinear mapping with emphasis on the distribution of samples on a plane of which the
base vectors are references of fluorescence. This paper describes an experiment with measurement of multiple
fluorescence and compensation using a conventional method and our proposed method. Results show that
multiple fluorescence is not always able to assume a linear combination model. Moreover, we confirmed that the
presented method is independent of linearity of multiple fluorescence.