Automated delineation of non-small cell lung cancer: A step toward quantitative reasoning in medical decision science

Quantitative reasoning in medical decision science relies on the delineation of pathological objects. For example, evidence-based clinical decisions regarding lung diseases require the segmentation of nodules, tumors, or cancers. Non-small cell lung cancer (NSCLC) tends to be large sized, irregularly shaped, and grows against surrounding structures imposing challenges in the segmentation, even for expert clinicians. An automated delineation tool based on spatial analysis was developed and studied on 25 sets of computed tomography scans of NSCLC. Manual and automated delineations were compared, and the proposed method exhibited robustness in terms of the tumor size (5.32–18.24 mm), shape (spherical or irregular), contouring (lobulated, spiculated, or cavitated), localization (solitary, pleural, mediastinal, endobronchial, or tagging), and laterality (left or right lobe) with accuracy between 80% and 99%. Small discrepancies observed between the manual and automated delineations may arise from the variability in the practitioners' definitions of region of interest or imaging artifacts that reduced the tissue resolution.     

The influence of calcination temperature on catalytic activities in a Co based catalyst for CO2 dry reforming

The carbon dioxide dry reforming of methane (CDR) reaction could be thermodynamically favored in the range of 800 to 1,000 °C. However, the catalyst in this reaction should be avoided at the calcination temperature over 800 °C since strong metal support interaction (SMSI) in this temperature range can decrease activity due to loss of active sites. Therefore, we focused on optimizing the temperature of pretreatment and a comparison of surface characterization results for CDR. Results related to metal sintering over support, re-dispersion by changing of particle size of metal-support, and strong metal support interaction were observed and confirmed in this work. In our conclusion, optimum calcination temperature for a preparation of catalyst was proposed that 400 °C showed a higher and more stable catalytic activity without changing of support characteristics.     

Synthesis of mesoporous tungsten oxide nanofibers using the electrospinning method

Mesoporous tungsten oxide nanofibers were synthesized via a 500 °C thermal treatment of composite nanofibers prepared by electrospinning an ethanol solution consisting of tungsten ethoxide, P123 triblock copolymer, and polyvinylpyrrolidone. The as-electrospun composites exhibited unwoven nanofibers with an average diameter of 233 nm and a smooth surface morphology. During the calcination process, the composite nanofibers were shrunk to 85 nm in diameter and converted into rough, wormhole-like nanofibers. These were formed by agglomerating polycrystalline WO₃ particles of 10–30 nm along the axial direction. Furthermore, a measured pore-size distribution indicated that this nanofiber mat had different types of meso-sized porosities, which may have resulted from their wormhole-like structures and inter-fiber voids. In addition, it was observed to have the intra-grain porosity with the diameter of about 1.0 nm.     

Optimal depth estimation by combining focus measures using genetic programming

Three-dimensional (3D) shape reconstruction is a fundamental problem in machine vision applications. Shape From Focus (SFF) is one of the passive optical methods for 3D shape recovery that uses degree of focus as a cue to estimate 3D shape. In this approach, usually a single focus measure operator is applied to measure the focus quality of each pixel in the image sequence. However, the applicability of a single focus measure is limited to estimate accurately the depth map for diverse type of real objects. To address this problem, we develop Optimal Composite Depth (OCD) function through genetic programming (GP) for accurate depth estimation. The OCD function is constructed by optimally combining the primary information extracted using one/or more focus measures. The genetically developed composite function is then used to compute the optimal depth map of objects. The performance of the developed nonlinear function is investigated using both the synthetic and the real world image sequences. Experimental results demonstrate that the proposed estimator is more useful in computing accurate depth maps as compared to the existing SFF methods. Moreover, it is found that the heterogeneous function is more effective than homogeneous function.     

A novel algorithm for estimation of depth map using image focus for 3D shape recovery in the presence of noise

Three-dimensional shape recovery from one or multiple observations is a challenging problem of computer vision. In this paper, we present a new Focus Measure for the estimation of a depth map using image focus. This depth map can subsequently be used in techniques and algorithms leading to the recovery of a three-dimensional structure of the object, a requirement of a number of high level vision applications. The proposed Focus Measure has shown robustness in the presence of noise as compared to the earlier Focus Measures. This new Focus Measure is based on an optical transfer function implemented in the Fourier domain. The results of the proposed Focus Measure have shown drastic improvements in estimation of a depth map, with respect to the earlier Focus Measures, in the presence of various types of noise including Gaussian, Shot, and Speckle noises. The results of a range of Focus Measures are compared using root mean square error and correlation metric measures.     

Fabrication of SiO2-ZrO2 composite fiber mats via electrospinning

(1 ? x)SiO₂-(x)ZrO₂ (x = 0.1, 0.2) composite fiber mats were prepared by electrospinning their sol-gel precursors of zirconium acetate and tetraethyl orthosilicate (TEOS) without using a polymer binder. The electrospun composite fibers were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FT-IR) and mercury porosimetry. The composite fibers having a tetragonal crystalline ZrO₂ were obtained by calcining the electrospun composite fibers at high temperatures. The results show that the structure and crystallization of ZrO₂ in the composite fibers can be controlled by sintering temperature, while the porosity and morphology of the fiber mats did not depend on the sintering temperature.     

Fabrication of SiO2-ZrO2 composite fiber mats via electrospinning

(1 − x)SiO₂-(x)ZrO₂ (x = 0.1, 0.2) composite fiber mats were prepared by electrospinning their sol-gel precursors of zirconium acetate and tetraethyl orthosilicate (TEOS) without using a polymer binder. The electrospun composite fibers were characterized by powder X-ray diffraction (XRD), scanning electron microscopy (SEM), fourier transform infrared spectroscopy (FT-IR) and mercury porosimetry. The composite fibers having a tetragonal crystalline ZrO₂ were obtained by calcining the electrospun composite fibers at high temperatures. The results show that the structure and crystallization of ZrO₂ in the composite fibers can be controlled by sintering temperature, while the porosity and morphology of the fiber mats did not depend on the sintering temperature.     

Searching surface orientation of microscopic objects for accurate 3D shape recovery

In this article, we propose a new shape from focus (SFF) method to estimate 3D shape of microscopic objects using surface orientation cue of each object patch. Most of the SFF algorithms compute the focus value of a pixel from the information of neighboring pixels lying on the same image frame based on an assumption that the small object patch corresponding to the small neighborhood of a pixel is a plane parallel to the focal plane. However, this assumption fails in the optics with limited depth of field where the neighboring pixels of an image have different degree of focus. To overcome this problem, we try to search the surface orientation of the small object patch corresponding to each pixel in the image sequence. Searching of the surface orientation is done indirectly by principal component analysis. Then, the focus value of each pixel is computed from the neighboring pixels lying on the surface perpendicular to the corresponding surface orientation. Experimental results on synthetic and real microscopic objects show that the proposed method produces more accurate 3D shape in comparison to the existing techniques.     

MEMS needle-type sensor array for in situ measurements of dissolved oxygen and redox potential

Microelectrodes are among the most accurate and reliable monitoring devices for measuring the dynamics of biofilm processes. This paper describes a novel needle-type microelectrode array (MEA) for simultaneous in situ measurements of dissolved oxygen (DO) and oxidation reduction potential (ORP) fabricated using microelectromechanical systems (MEMS) technologies. The MEA exhibits fast response times for both DO and ORP measurements and shows a substantial increase in DO sensitivity. To demonstrate the versatility of the new sensor, it was applied to the measurement of DO and ORP microprofiles in a multispecies biofilm. This work demonstrates that the MEA is able to monitor local concentration changes with a high spatial resolution and provide the versatility of the microelectrode technique needed for biofilm studies as well as the capability for repetitive measurements. In addition, the use of MEMS technologies and batch fabrication approaches enables integration, high consistency, high yields, and mass production. With further development, it may be possible to add additional sensors to the MEA (e.g., pH, phosphate) and integrate them with a reference electrode.