  Near infrared diffuse optical tomography (DOT) provides an imaging modality
for the oxygenation of tissue. In this paper, we propose a novel machine
learning algorithm based on time-domain radiative transfer equation. We use
temporal profiles of absorption measure for a two-dimensional model of target
tissue, which are calculated by solving time-domain radiative transfer
equation. Applying a long-short-term memory (LSTM) deep learning method, we
find that we can specify positions of cancer cells with high accuracy rates. We
demonstrate that the present algorithm can also predict multiple or extended
cancer cells.
