High-performance reconstruction of CT medical images by using out-of-core methods in GPU.

Background And Objective: Since Computed Tomography (CT) is one of the most widely used medical imaging tests, it is essential to work on methods that reduce the radiation the patient is exposed to. Although there are several possible approaches to achieve this, we focus on reducing the exposure time through sparse sampling. With this approach, efficient algebraic methods are needed to be able to generate the images in real time, and since their computational cost is high, using high-performance computing is essential.

Computed tomography medical image reconstruction on affordable equipment by using Out-Of-Core techniques.

Background And Objective: As Computed Tomography scans are an essential medical test, many techniques have been proposed to reconstruct high-quality images using a smaller amount of radiation. One approach is to employ algebraic factorization methods to reconstruct the images, using fewer views than the traditional analytical methods. However, their main drawback is the high computational cost and hence the time needed to obtain the images, which is critical in the daily clinical practice.

Evaluation of image filters for their integration with LSQR computerized tomography reconstruction method.

In CT (computerized tomography) imaging reconstruction, the acquired sinograms are usually noisy, so artifacts will appear on the resulting images. Thus, it is necessary to find the adequate filters to combine with reconstruction methods that eliminate the greater amount of noise possible without altering in excess the information that the image contains. The present work is focused on the evaluation of several filtering techniques applied in the elimination of artifacts present in CT sinograms.

Medical image restoration with different types of noise.

The images obtained by X-Ray or computed tomography (CT) in adverse conditions may be contaminated with noise that can affect the detection of diseases. A large number of image processing techniques (filters) have been proposed to remove noise. These techniques depend on the type of noise present in the image.

Estimated radiation dose reduction using non-linear diffusion method in computed radiography.

In this paper we use a non-linear diffusion method to filter the inherent noise in a Computed Radiography (CR) for reducing the dose absorbed by the patients especially children in pediatric applications, related with the exposure mAs. The method is implemented in order to create a lower CR dose based on the selection of lower X-ray exposure and with a reduction of the noise using a non-linear diffusion method. The impact of several milliAmpere-seconds (mAs) setting on image quality has been studied using the RANDO phantom.

[Hyperandrogenic syndrome in a postmenopausal woman: a case report].

Hyperandrogenic syndromes include diseases that manifest through an increased biological activity of androgens and that can originate from neoplastic or functional diseases. Androgen-secreting ovarian tumors represent about 1% of ovarian neoplasias. Steroid cell tumors are among the more rare types which account for less than 0.