Reducing windmill artifacts in clinical spiral CT using a deep learning-based projection raw data upsampling: Method and robustness evaluation.

Background: Multislice spiral computed tomography (MSCT) requires an interpolation between adjacent detector rows during backprojection. Not satisfying the Nyquist sampling condition along the z-axis results in aliasing effects, also known as windmill artifacts. These image distortions are characterized by bright streaks diverging from high contrast structures.

Raw data consistent deep learning-based field of view extension for dual-source dual-energy CT.

Background: Due to technical constraints, dual-source dual-energy CT scans may lack spectral information in the periphery of the patient.

Purpose: Here, we propose a deep learning-based iterative reconstruction to recover the missing spectral information outside the field of measurement (FOM) of the second source-detector pair.

Methods: In today's Siemens dual-source CT systems, one source-detector pair (referred to as A) typically has a FOM of about 50 cm, while the FOM of the other pair (referred to as B) is limited by technical constraints to a diameter of about 35 cm.

Deep learning-based extended field of view computed tomography image reconstruction: influence of network design on image estimation outside the scan field of view.

The problem of data truncation in Computed Tomography (CT) is caused by the missing data when the patient exceeds the Scan Field of View (SFOV) of a CT scanner. The reconstruction of a truncated scan produces severe truncation artifacts both inside and outside the SFOV. We have employed a deep learning-based approach to extend the field of view and suppress truncation artifacts.

Motion compensation for aortic valves using partial angle CT reconstructions.

Purpose: A motion compensation method that is aimed at correcting motion artifacts of cardiac valves is proposed. The primary focus is the aortic valve.

Methods: The method is based around partial angle reconstructions and a cost function including the image entropy.

Deep learning-based forward and cross-scatter correction in dual-source CT.

Purpose: Dual-source computed tomography (DSCT) uses two source-detector pairs offset by about 90°. In addition to the well-known forward scatter, a special issue in DSCT is cross-scattered radiation from X-ray tube A detected in the detector of system B and vice versa. This effect can lead to artifacts and reduction of the contrast-to-noise ratio of the images.

Evaluation of novel AI-based extended field-of-view CT reconstructions.

Purpose: Modern computed tomography (CT) scanners have an extended field-of-view (eFoV) for reconstructing images up to the bore size, which is relevant for patients with higher BMI or non-isocentric positioning due to fixation devices. However, the accuracy of the image reconstruction in eFoV is not well known since truncated data are used. This study introduces a new deep learning-based algorithm for extended field-of-view reconstruction and evaluates the accuracy of the eFoV reconstruction focusing on aspects relevant for radiotherapy.

Deep learning-based coronary artery motion estimation and compensation for short-scan cardiac CT.

Purpose: During a typical cardiac short scan, the heart can move several millimeters. As a result, the corresponding CT reconstructions may be corrupted by motion artifacts. Especially the assessment of small structures, such as the coronary arteries, is potentially impaired by the presence of these artifacts.

The impact of polymer selection and dose on the incorporation of ballasting agents onto wastewater aggregates.

Ballasted flocculation is an efficient high-rate sedimentation process getting more attention as an advanced P removal technology for levels below 0.1 mg/L. The process is well-known yet only very few studies have investigated the interactions, within the matrix of wastewater, of coagulant, polymer and ballast, especially when it comes to polymer doses and types which are, in the industry, rather based on recommendations than scientific evidence.

Stack transition artifact removal (STAR) for cardiac CT.

Introduction: In cardiac computed tomography (CT), irregular motion may lead to unique artifacts for scanners with a longitudinal collimation that does not cover the entire heart. Given partial coverage, subvolumes, or stacks, may be reconstructed and used to assemble a final CT volume. Irregular motion, for example, due to cardiac arrhythmia or breathing, may cause mismatch between neighboring stacks and therefore discontinuities within the final CT volume.

"X-Map 2.0" for Edema Signal Enhancement for Acute Ischemic Stroke Using Non-Contrast-Enhanced Dual-Energy Computed Tomography.

Objectives: A novel imaging technique ("X-map") has been developed to identify acute ischemic lesions for stroke patients using non-contrast-enhanced dual-energy computed tomography (NE-DE-CT). Using the 3-material decomposition technique, the original X-map ("X-map 1.0") eliminates fat and bone from the images, suppresses the gray matter (GM)-white matter (WM) tissue contrast, and makes signals of edema induced by severe ischemia easier to detect.

[French radiotherapy database: results of a survey of French radiation oncology centers in 2007].

For the second year, the French Radiotherapy Database presents information from French radiation oncology centers. Among 179 centers, 159 have participated (90 %). The number of accelerators increased from 371 to 384 between 2006 and 2007, 11 % of these machines are more than 15 years old.

The CD8 T cell compartment plays a dominant role in the deficiency of Brown-Norway rats to mount a proper type 1 immune response.

Differential cytokine production by T cells plays an important role in regulating the nature of an immune response. In the rat, Brown-Norway (BN) and Lewis (LEW) strains differ markedly in their susceptibility to develop either type 1 or type 2-mediated autoimmune manifestations. BN rats are susceptible to type 2-dependent systemic autoimmunity, while LEW rats are resistant.

An in vivo model for the experimental selection of drugs able to prevent immune complex glomerulonephritis.

Polyclonal activation of lymphocytes and immune complex-mediated glomerular lesions were induced in C57Bl/6 mice by injecting bacterial lipopolysaccharide (LPS) twice a week for 2 weeks. The usefulness of such a model for in vivo evaluation of immunomodulatory and therapeutic effects of drugs, was investigated by treating mice with DIAM4, a cyclophosphazenic compound known to modulate polyclonal activation of lymphocytes and to prevent mouse lupus nephritis. Prevention of LPS-triggered lymphocyte polyclonal activation and glomerular lesions was observed in the DIAM4-treated mice.

Cloning of dapD, aroD and asd of Leptospira interrogans serovar icterohaemorrhagiae, and nucleotide sequence of the asd gene.

Metabolites such as diaminopimelate and some aromatic derivatives, not synthesized in mammalian cells, are essential for growth of bacteria. As a first step towards the design of a new human live vaccine that uses attenuated strains of Leptospira interrogans, the asd, aroD and dapD genes, encoding aspartate beta-semialdehyde dehydrogenase, 3-dehydroquinase and tetrahydrodipicolinate N-succinyltransferase, respectively, were cloned by complementation of Escherichia coli mutants. The complete nucleotide sequence of the asd gene was determined and found to contain an open reading frame capable of encoding a protein of 349 amino acids with a calculated Mr of 38,007.

rRNA gene restriction patterns of Leptospira: a molecular typing system.

A total of 67 serovar reference strains and 7 isolates belonging to the genus Leptospira were characterized by ribosomal ribonucleic acid (rRNA) gene restriction patterns. Fifty patterns were observed. Strains belonging to different genomic species always gave different patterns.