Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models.

Multiphase CT scanning of the liver is performed for several clinical applications; however, radiation exposure from CT scanning poses a nontrivial cancer risk to the patients. The radiation dose may be reduced by determining the scan range of the subsequent scans by the location of the target of interest in the first scan phase. The purpose of this study is to present and assess an automatic method for determining the scan range for multiphase CT scans. Our strategy is to first apply a CNN-based method for detecting the liver in 2D slices, and to use a liver range search algorithm for detecting the liver range in the scout volume. The target liver scan range for subsequent scans can be obtained by adding safety margins achieved from Gaussian liver motion models to the scan range determined from the scout. Experiments were performed on 657 multiphase CT volumes obtained from multiple hospitals. The experiment shows that the proposed liver detection method can detect the liver in 223 out of a total of 224 3D volumes on average within one second, with mean intersection of union, wall distance and centroid distance of 85.5%, 5.7 mm and 9.7 mm, respectively. In addition, the performance of the proposed liver detection method is comparable to the best of the state-of-the-art 3D liver detectors in the liver detection accuracy while it requires less processing time. Furthermore, we apply the liver scan range generation method on the liver CT images acquired from radiofrequency ablation and Y-90 transarterial radioembolization (selective internal radiation therapy) interventions of 46 patients from two hospitals. The result shows that the automatic scan range generation can significantly reduce the effective radiation dose by an average of 14.5% (2.56 mSv) compared to manual performance by the radiographer from Y-90 transarterial radioembolization, while no statistically significant difference in performance was found with the CT images from intra RFA intervention (p = 0.81). Finally, three radiologists assess both the original and the range-reduced images for evaluating the effect of the range reduction method on their clinical decisions. We conclude that the automatic liver scan range generation method is able to reduce excess radiation compared to the manual performance with a high accuracy and without penalizing the clinical decision

Mass Transportation for Deformable Image Registration with Application to Lung CT

Computed Tomography (CT) of the lungs play a key role in clinical investigation of thoracic malignancies, as well as having the potential to increase our knowledge about pulmonary diseases including cancer. It enables longitudinal trials to monitor lung disease progression, and to inform assessment of lung damage resulting from radiation therapy. We present a novel deformable image registration method that accommodates changes in the density of lung tissue depending on the amount of air present in the lungs inspiration/expiration state. We investigate the Monge-Kantorovich theory of optimal mass transportation to model the appearance of lung tissue and apply it in a method for registration. To validate the model, we apply our method to an inhale and exhale lung CT data set, and compare it against registration using the sum of squared differences (SSD) as a representative of the most popular similarity measures used in deformable image registration. The results show that the developed registration method has the potential to handle intensity distortions caused by air and tissue compression, and in addition it can provide accurate annotations of the lungs

Recent Advances in Sugarcane Industry Solid By-Products Valorization

Sugarcane is among the leading agricultural crop cultivated in tropical regions of the world. Industrial processing of sugarcane generates sugar; as well as various solid wastes (i.e. sugarcane bagasse, pressmud). Improvement of biotechnology in industrial level, offers opportunities for economic utilization of these solid residues. In the last few decades, sugarcane bagasse and pressmud have been explored in the theme of lignocellulosic bioconversion. The recalcitrance of biomass is a major drawback towards successful exploitation of lignocellulosic residues. Pretreatment by suitable/efficient processes can overcome this limitation. In this regards; physical, chemical and biological treatment systems are brought into our perspective. Chemical and physicochemical methods are capital-intensive but not environment-friendly, in contrast, method like biological treatment is eco-friendly but extremely slow. There are still major technological and economic challenges need to be addressed; e.g. bioprospecting, established more reliable genetically modified microorganisms, upgrade gene cloning and sequencing processes, yield improvement at large scale etc. Productions of value-added products from these solid wastes are discussed in such a way that pinpoints the most recent trends and the future directions. Biofuels, enzymes, organic acids and bio-sorbents production draw a clear sketch of the current and future bio-based products. Nano-biotechnology and genetic engineering could be future trends to improved processes and products. This review serves as a valuable reference material for a wide range of scientists and technologists in the relevant fields