Automated processing of series of micro-CT scans

For some applications of high-resolution X-ray Tomography (micro-CT) scanning, a large set of similar samples is to be analyzed in order to obtain statistically significant results. The complete process, including the micro-CT scan itself, the reconstruction and the analysis is almost identical for every sample. However, in a typical workflow every step is manually performed for every individual sample. This could be optimised by automation of this process, which results in less human intervention and thus a smaller cost and a lower risk to human error. We developed a reliable method to semi-automatically scan several stacked samples and automatically reconstruct the resulting series of data sets. The reconstruction step includes the manual reconstruction of one data set in order to optimize the reconstruction parameters, which can then be used for the rest of the batch. In future work, the automatic handling of the next step in the micro-CT workflow, 3D analysis, will also be improved

Comparing Image Quality in Phase Contrast subμ\mu X-Ray Tomography -- A Round-Robin Study

How to evaluate and compare image quality from different sub-micrometer (sub$\mu$) CT scans? A simple test phantom made of polymer microbeads is used for recording projection images as well as 13 CT scans in a number of commercial and non-commercial scanners. From the resulting CT images, signal and noise power spectra are modeled for estimating volume signal-to-noise ratios (3D SNR spectra). Using the same CT images, a time- and shape-independent transfer function (MTF) is computed for each scan, including phase contrast effects and image blur ($\mathrm{MTF_{blur}}$). The SNR spectra and MTF of the CT scans are compared to 2D SNR spectra of the projection images. In contrary to 2D SNR, volume SNR can be normalized with respect to the object's power spectrum, yielding detection effectiveness (DE) a new measure which reveals how technical differences as well as operator-choices strongly influence scan quality for a given measurement time. Using DE, both source-based and detector-based sub$\mu$ CT scanners can be studied and their scan quality can be compared. Future application of this work requires a particular scan acquisition scheme which will allow for measuring 3D signal-to-noise ratios, making the model fit for 3D noise power spectra obsolete

Evaluation of human obstructive sleep apnea using computational fluid dynamics.

Obstructive sleep apnea (OSA) severity might be correlated to the flow characteristics of the upper airways. We aimed to investigate the severity of OSA based on 3D models constructed from CT scans coupled with computational fluid dynamics (CFD) simulations. The CT scans of seven adult patients diagnosed with OSA were used to reconstruct the 3D models of the upper airways and CFD modeling and analyses were performed. Results from the fluid simulations were compared with the apnea-hypopnea index. Here we show a correlation between a CFD-based parameter, the adjusted pressure coefficient (Cp*), and the respective apnea-hypopnea index (Pearson's r = 0.91, p = 0.004), which suggests that the anatomical-based model coupled with CFD could provide functional and localized information for different regions of the upper airways

Revue Des Doses d’Exposition Et Des Methode d’Optimisation En Tomodensitometrie (TDM) De l’Enfant Au Togo

Objectives: To assess the justification of indications of CT scans and the exposure doses of children during CT scans. Methods: Prospective study of 104 CT-sans of children collected over a period of 6 months. Results: Female children were predominant with a sex ratio female / male of 1.2. The predominant age group was the 10 to 15 years (41%). The CT-Scan of the head was the most practiced exam, with 64.42% (67/104). When analyzing information according to the recommendations of the Guide of well practices of French Society of Radiology (SFR) and the French Society of Biophysics and Nuclear Medicine (SFBMN), only 77% of CT-Scans were justified. Almost half (49.04%) of CT-Scans had a CT-Dose Index (CTDI) and Dose Length Product (DLP) greater than the French reference norms defined for each group of age. The average values of CTDI and DLP are above the norms for all CT-scans of the skull, facial bones and sinuses. Conclusion: The doses administered to children by CT-Scans are above accepted norms. Improved practices continue medical training of radiology manipulators and the creation of a regulatory or an agency of radioprotection is necessary

Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions

Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans acquired in screening enable quantification of atherosclerotic calcifications and thus enable identification of subjects at increased cardiovascular risk. This paper presents a method for automatic detection of coronary artery, thoracic aorta and cardiac valve calcifications in low-dose chest CT using two consecutive convolutional neural networks. The first network identifies and labels potential calcifications according to their anatomical location and the second network identifies true calcifications among the detected candidates. This method was trained and evaluated on a set of 1744 CT scans from the National Lung Screening Trial. To determine whether any reconstruction or only images reconstructed with soft tissue filters can be used for calcification detection, we evaluated the method on soft and medium/sharp filter reconstructions separately. On soft filter reconstructions, the method achieved F1 scores of 0.89, 0.89, 0.67, and 0.55 for coronary artery, thoracic aorta, aortic valve and mitral valve calcifications, respectively. On sharp filter reconstructions, the F1 scores were 0.84, 0.81, 0.64, and 0.66, respectively. Linearly weighted kappa coefficients for risk category assignment based on per subject coronary artery calcium were 0.91 and 0.90 for soft and sharp filter reconstructions, respectively. These results demonstrate that the presented method enables reliable automatic cardiovascular risk assessment in all low-dose chest CT scans acquired for lung cancer screening

Computer-aided segmentation and estimation of indices in brain CT scans

The importance of neuro-imaging as one of the biomarkers for diagnosis and prognosis of pathologies and traumatic cases is well established. Doctors routinely perform linear measurements on neuro-images to ascertain severity and extent of the pathology or trauma from significant anatomical changes. However, it is a tedious and time consuming process and manually assessing and reporting on large volume of data is fraught with errors and variation. In this paper we present a novel technique for segmentation of significant anatomical landmarks using artificial neural networks and estimation of various ratios and indices performed on brain CT scans. The proposed method is efficient and robust in detecting and measuring sizes of anatomical structures on non-contrast CT scans and has been evaluated on images from subjects with ages between 5 to 85 years. Results show that our method has average ICC of ≥0.97 and, hence, can be used in processing data for further use in research and clinical environment

Radiation dose differences between thoracic radiotherapy planning CT and thoracic diagnostic CT scans

Purpose: To compare the absorbed dose from computed tomography (CT) in radiotherapy planning (RP CT) against those from diagnostic CT (DG CT) examinations and to explore the possible reasons for any dose differences. Method: Two groups of patients underwent CT-scans of the thorax with either DG-CT (n=55) or RP-CT (n=55). Patients from each group had similar weight and body mass index (BMI) and were divided into low (25). Parameters including CTDIvol, DLP and scan length were compared. Results: The mean CTDIvol and DLP values from RP-CT (38.1 mGy, 1472 mGy·cm) are approximately four times higher than for DG-CT (9.63 mGy, 376.5 mGy·cm). For low BMI group, the CTDIvol in the RP-CT scans (36.4 mGy) is 6.3 times higher than the one in the DG-CT scans (5.8 mGy). For high BMI group, the CTDIvol in the RP-CT (39.6 mGy) is 2.5 times higher than the one in the DG-CT scans (15.8 mGy). In the DG-CT scans a strong negative linear correlation between noise index (NI) and mean CTDIvol was observed (r =-0.954, p=0.004); the higher NI, the lower CTDIvol. This was not the case in the RP-DG scans. Conclusion: The absorbed radiation dose is significantly higher and less BMI dependent for RP-CT scans compared to DG-CT. Image quality requirements of the examinations should be researched to ensure that radiation doses are not unnecessarily high