Investigation of the imaging quality of synchrotron-based phase-contrast mammographic tomography

Abstract

We report the results of a systematic study of phase-contrast X-ray computed tomography in the propagation-based and the analyser-based modes using specially designed phantoms and excised breast tissue samples. The study is aimed at quantitative evaluation and subsequent optimisation, with respect to detection of small tumours in breast tissue, of the effects of phase contrast and phase retrieval on key imaging parameters, such as spatial resolution, contrast-to-noise ratio, X-ray dose and a recently proposed "intrinsic quality" characteristic which combines the image noise with the spatial resolution. We demonstrate that some of the methods evaluated in this work lead to substantial (more than 20-fold) improvement in the contrast-to-noise and intrinsic quality of the reconstructed tomographic images compared to conventional techniques, with the measured characteristics being in good agreement with the corresponding theoretical estimations. This improvement also corresponds to an approximately 400-fold reduction in the X-ray dose, compared to conventional absorption-based tomography, without a loss in the imaging quality. The results of this study confirm and quantify the significant potential benefits achievable in 3D mammography using X-ray phase-contrast imaging and phase-retrieval techniques.

On the noise-resolution duality, Heisenberg uncertainty and Shannon's information

“…We showed that our inequality (14) potentially provides a more accurate lower bound for the phase-space volume (which quantifies the Heisenberg uncertainty) than the conventional uncertainty relationship (7). The new lower bound is related to the phase-space noise-to-signal ratio (15) of a given imaging/measuring system.…”

“…These two characteristics, and the interplay between them, attained additional relevance in recent years in the context of biomedical imaging, where the samples are often sensitive to the radiation dose [15], in certain astronomical methods where the detectable photon flux can be extremely low [10], as well as in some other problems, including those related to the foundations of quantum physics [1]. In x-ray medical imaging, in particular, it is critically important to minimize the radiation dose delivered to the patient, while still being able to obtain 2D or 3D images with sufficient spatial resolution and large C3 enough snr to detect the features of interest, such as small tumours [13,14]. In this context, an imaging system (e.g., a ct scanner) must maximize the amount of relevant information extractable from the collected images, while keeping sufficiently low the number of x-ray photons impinging on the patient.…”

“…Gureyev et al [13,14] recently introduced a dimensionless 'intrinsic quality' characteristic Q S which incorporates both the noise propagation and the spatial resolution properties of a linear shift-invariant (lsi) imaging system:…”

“…Gureyev et al [13,14] assumed that the incident fluence corresponds to a spatially stationary and uncorrelated random process with Poisson statistics, hence snr…”

“…Because Q S is normalised with respect to the incident fluence, it may be viewed as 'imaging quality per single incident particle'. In practice, if the incident fluence rate or the exposure time is increased, then the quality of the resultant image is expected to increase too (normally in proportion to F 1/2 in ) [13,14]. However, in applications where the imaging quanta are at premium (e.g., in low-light imaging) or where the irradiation dose delivered to the sample is critical (as in x-ray or electron imaging of biological samples), Q S represents a key performance indicator of the imaging system.…”