Analysis of the Application Value of X-Ray Digital Tomographic Fusion Technique in Urinary System Diseases

Objective. To explore the application value of the X-ray digital tomographic fusion technique in the diagnosis of urinary system diseases. Methods. 500 patients with suspected urinary diseases in our hospital were examined by three methods: X-ray digital tomographic fusion imaging (DTS), intravenous pyelography (IVP), and abdominal plain film (KUB), and the image quality before and after tomographic fusion was objectively evaluated. The image quality could be divided into three grades: excellent, good, and poor. Results. The image excellent rate of DTS (88%) was higher than that of IVP (27.5%). The sensitivity of DTS in the diagnosis of renal cyst and space occupying of the bladder was higher than that of IVP ( P < 0.05 ). The accuracy rate of DTS in the diagnosis of urinary calculi was 93.33%, higher than 63.3% of KUB ( P < 0.001 ). The accuracy rate of DTS in the diagnosis of ureteral stricture was 90%, higher than 65% of IVP ( P = 0.03 ). The accuracy of DTS in the diagnosis of hydronephrosis was higher than that of IVP and KUB ( P < 0.05 ). Conclusion. In the examination of urinary system-related diseases, high-definition images can be obtained by timely using sectional fusion technology. Compared with conventional IVP, space occupying lesions such as the bladder and kidney can be displayed more clearly with the help of the tomographic fusion technique, which is helpful to improve the possibility of finding lesions and is of great significance in clinical application.

Object-Based Land Cover Classification Using Multisensor Remote Sensing Data

The goal of this chapter is to demonstrate the classification of natural and man-made objects from multisensory remote sensing data. The spectral and spatial features play an important role in extracting the information of natural and man-made objects. The classification accuracy may be enhanced by fusion technique applied on feature knowledge database. A significantly different approach has been devised using spatial as well as spectral features from multisensory data, and the classified results are enhanced by majority voting fusion technique. The author concludes by presenting extensive discussion at each level and has envisaged the potential use of multisensory data for object-based land cover classification.

Efficient Pre-Processing and Segmentation for Lung Cancer Detection Using Fused CT Images

Over the last two decades, radiologists have been using multi-view images to detect tumors. Computer Tomography (CT) imaging is considered as one of the reliable imaging techniques. Many medical-image-processing techniques have been developed to diagnoses lung cancer at early or later stages through CT images; however, it is still a big challenge to improve the accuracy and sensitivity of the algorithms. In this paper, we propose an algorithm based on image fusion for lung segmentation to optimize lung cancer diagnosis. The image fusion technique was developed through Laplacian Pyramid (LP) decomposition along with Adaptive Sparse Representation (ASR). The suggested fusion technique fragments medical images into different sizes using the LP. After that, the LP is used to fuse the four decomposed layers. For the evaluation purposes of the proposed technique, the Lungs Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) was used. The results showed that the Dice Similarity Coefficient (DSC) index of our proposed method was 0.9929, which is better than recently published results. Furthermore, the values of other evaluation parameters such as the sensitivity, specificity, and accuracy were 89%, 98% and 99%, respectively, which are also competitive with the recently published results.

Enhancing Downstream Processing Of Algal-Based Biofuel Using Novel Fused Bacteria And Green Solvents

The present study investigated the utilization of algal biomass to produce bio-oil and acetone, butanol, and ethanol (ABE) products. Novel Clostridia fusants (C. beijernickii + C. thermocellum-CbCt and C. acetobutylicum + C. thermocellocum-CaCt) were developed using protoplast fusion technique and subsequently subjected to UV radiation for strain enhancement. Resultant mutated fusants showed improvement in thermal stability and higher resistance to biobutanol toxicity. Algal biomass was initially subjected to various hydrolysis treatments prior to fermentation. Combination treatment of thermal, chemical, and enzymatic resulted in maximum sugar release of 27.78 g/L. Maximum biobutanol concentration from fermentation using CbCt resulted in 7.98 g/L. Fermentation using CaCt produced a concentration of 7.39 g/L. Oil extraction from virgin algae investigated a green, bio-based approach using terpenes with ultrasonication and a modified, Bligh and Dyer method, separately. Combination method, ultrasonication followed by the modified Bligh and Dyer, resulted in oil yield of 46.27% (dlimonene) and 39.85% (p-cymene). Oil extraction was also produced from an algae sample following fermentation. Combined extraction method using fermentation sample resulted in oil yield of 65.04%.

Enhancing Downstream Processing Of Algal-Based Biofuel Using Novel Fused Bacteria And Green Solvents

The present study investigated the utilization of algal biomass to produce bio-oil and acetone, butanol, and ethanol (ABE) products. Novel Clostridia fusants (C. beijernickii + C. thermocellum-CbCt and C. acetobutylicum + C. thermocellocum-CaCt) were developed using protoplast fusion technique and subsequently subjected to UV radiation for strain enhancement. Resultant mutated fusants showed improvement in thermal stability and higher resistance to biobutanol toxicity. Algal biomass was initially subjected to various hydrolysis treatments prior to fermentation. Combination treatment of thermal, chemical, and enzymatic resulted in maximum sugar release of 27.78 g/L. Maximum biobutanol concentration from fermentation using CbCt resulted in 7.98 g/L. Fermentation using CaCt produced a concentration of 7.39 g/L. Oil extraction from virgin algae investigated a green, bio-based approach using terpenes with ultrasonication and a modified, Bligh and Dyer method, separately. Combination method, ultrasonication followed by the modified Bligh and Dyer, resulted in oil yield of 46.27% (dlimonene) and 39.85% (p-cymene). Oil extraction was also produced from an algae sample following fermentation. Combined extraction method using fermentation sample resulted in oil yield of 65.04%.