Binary objects tomographic reconstruction from few noisy X-ray radiographs using a region based curve evolution method

This paper addresses tomographic reconstruction of binary objects from a small number of noisy projections in applications where the global dose remains constant with an increase or a decrease of the number of projections. A region based reconstruction method using curve evolution is proposed. To manage the lack of data, the tomographic reconstruction problem is defined as a domain optimization problem. A geometrical criterion directly embedded in a dynamical scheme is defined. The minimization of this criterion drives the region determination. This scheme is implemented using a level set method including regularization via local curvature. The quality of objects reconstructed from noiseless projections is satisfying even without regularization. However when the number of projections or the signal to noise ratio is decreased, reconstructed images suffer from geometrical degradations. We show the improvement of the results brought by regularization in drastic conditions such as reconstruction from three noisy projections.