A new technique for measuring hand volumes using Archimedes principle is described. The technique involves the immersion of a hand in a water container placed on an electronic balance. The volume is given by the change in weight divided by the density of water. This technique was compared with the more conventional technique of immersing an object in a container with an overflow spout and collecting and weighing the volume of overflow water. The hand volume of two subjects was measured. Hand volumes were 494 +/- 6 ml and 312 +/- 7 ml for the immersion method and 476 +/- 14 ml and 302 +/- 8 ml for the overflow method for the two subjects respectively. Using plastic test objects, the mean difference between the actual and measured volume was -0.3% and 2.0% for the immersion and overflow techniques respectively. This study shows that hand volumes can be obtained more quickly than the overflow method. The technique could find an application in clinics where frequent hand volumes are required.

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.

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