Breast cancer has been one of the leading causes of cancer deaths for females in the developed countries, including
the US. While early detection of breast cancer is essential for the reduction of death rate, there may be already more
than 107 cells in a breast cancer when it can be observed by X-ray mammogram. As contrast, the passive IR spectrogram
proposed by Szu et al. was shown to be promising in detecting the breast cancer several months ahead of mammogram.
With the energy readings from two IR cameras, one middle wavelength IR (MIR, 3 - 5μm) and one long wavelength IR
(LIR, 8 - 12μm), the IR spectrogram may be computed by using the blind source separation (BSS) algorithms developed
by Szu et al., which reveals the probability of being a cancer point on the breast surface. Two important tasks are
involved in computing the IR spectrogram. One is an accurate estimate of the ground state energy in the Helmholtz free
energy, H = E-T0S. The other is a correct pair-up of the points on the MIR and LIR images for a better estimation of
IR spectrogram. To minimize the probability of making an erroneous estimate of the ground state energy inherent in the
deterministic neighborhood-based BSS algorithm, a spatiotemporal approach is proposed in this paper. It takes into
account not only the neighborhood information but also the temporal information in determining the probability of being
a cancer point. Furthermore, a new sub-pixel super-resolution registration algorithm incorporating a third energy
dimension is proposed to establish better correspondences between the points in the MIR and LIR images. Phantom
study has confirmed that sub-pixel registration can be achieved by the proposed registration method. Human subject
study further shows that the breast cancer may be detected by the proposed spatiotemporal approach via
cross-referencing the IR spectrograms computed from the multiple pairs of MIR and LIR images taken at different times.
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