Reconstructing low-dose X-ray computed tomography (CT) images is a noise problem. This
work investigated a penalized weighted least-squares (PWLS) approach to address this …

Differentiation of malignant and benign pulmonary nodules is of paramount clinical importance.
Texture features of pulmonary nodules in CT images reflect a powerful character of the …

When excessive quantum noise is present in extremely low dose X-ray CT imaging, statistical
properties of the data has to be considered to achieve a satisfactory image reconstruction. …

Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated
image with some data and other constraints, piecewise-smooth x-ray computed …

Purpose: In current computed tomography (CT) examinations, the associated x‐ray
radiation dose is of a significant concern to patients and operators. A simple and cost‐effective …

Proton computed tomography (pCT) has the potential to improve the accuracy of dose
calculations for proton treatment planning, and will also be useful for pretreatment verification of …

Sparse-view CT reconstruction algorithms via total variation (TV) optimize the data iteratively
on the basis of a noise-and artifact-reducing model, resulting in significant radiation dose …

Purpose: Low‐dose x‐ray computed tomography (CT) is clinically desired. Accurate noise
modeling is a fundamental issue for low‐dose CT image reconstruction via statistics‐based …

In this paper, we introduce a concise and concrete definition of an accurate colon centerline
and provide an efficient automatic means to extract the centerline and its associated …

A statistical method is developed to classify tissue types and to segment the corresponding
tissue regions from relaxation time T/sub 1/, T/sub 2/, and proton density P/sub D/ weighted …