Estimating age from digital radiographic images of lumbar vertebrae in a Thai population using an image analysis technique

Using the lumbar vertebra for age estimation is helpful in cases when skeletal remains are incomplete and typical skeletal age indicators are absent. This study aimed to apply an image analysis method in extracting black pixel variables for age estimation by using the radiographic images of lumbar vertebra in a Thai population. All lumbar vertebrae L1–L5 of 220 (110 males and 110 females) from Thai individuals of known sex and ages were studied. The variables of Total Percentage of black pixels (TP), Mean Percentage of black pixels (MP), and Ratio of black to white pixels (BW), were calculated to assess the relationship between black pixel variables and aging. Equations were formulated using linear regression analysis. The results of this study indicated three variables of the lumbar vertebrae had significantly positive correlations with age. The correlation between parameters with age in males ranged 0.211–0.419, while the range in females was 0.219–0.458. The appropriate linear regression equation with the total and mean percentages of black pixel variables shows Age = −1.348+0.871 (TP) +0.514 (MP) of L4 for males (SEE; 15.4 years), and Age = 5.338 +0.316 (TP) +0.952 (MP) of L1 for females (SEE; 13.8 years). Age estimation using an image analysis method is an alternative to investigating the trabecular structure. The black pixel variable is not the actual value of bone density. However, it is useful to study its relationship with aging.

Technology for Conversion of Computer Tomography Results into Three-Dimensional Models

The development relates to information technology and can be used to process medical images. This task is achieved by the fact that DICOM files containing the results of computed tomography of the human head are subject to correction. They change the color of the pixels at the transition points from black to gray or vice versa, and also replace the black pixel with white. As a result, the percentage of loss of information about small bones is reduced from 22-31 % to 3-5 %, and, therefore, the accuracy of the three-dimensional model of the facial skull of the human head is increased. All this contributes to a significant improvement in the quality of facial surgery.

Analysis of Fuzzy Based Directional Median Filter with Mixed Noise

All the sources of digital images like camera as well as communication methods like wireless or wired communication leads to corruption of pixels of digital image. Usually digital image consists of values from 0 to 255 where 0 represents black pixel and 255 represents white pixel. Due to above sources and communication method, these pixels change there value which leads to change in the output values. Mixed noise is popular now a day which is a combination of Gaussian noise and salt & pepper noise. Median filters are popular in removing the noise from the digital images. Fuzzy based controllers are very popular now a day to solve issues better than others. In this paper, we have discussed fuzzy logic, median filter and directional median filter to remove the corrupted pixels out of digital image. Parameters like PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) are used for qualitative analysis of filter.

Measurement of the Active Toxoplasma Retinochoroiditis Lesion Size During the Disease Course With Swept Source Optical Coherence Tomography Angiography: A Retrospective Image Analysis

Purpose To measure the lesion size reduction in eyes with active toxoplasma retinochoroiditis during the disease course with swept- source optical coherence tomography angiography (SS-OCTA). Methods We retrospectively analyzed the chorioretinal lesion size in a group of 14 eyes with a single active toxoplasma retinochoroiditis lesion.SS-OCTA was performed at the baseline and follow -up in all eyes. The 6x6 mm choriocapillaris slab images were evaluated with an image analysis (Matlab). The number of black and white pixels in a 1500µm-diameter circle centered on each active lesion was counted at the time of baseline examination and at the first follow-up visit when the chorioretinal scar formation was noticed. Results Fourteen eyes with a single active toxoplasmosis retinochoroiditis lesion were included. Ten patients were female and three,male. Mean age was 29.1 ± 14.9 years. Active lesions were at the macula in five eyes, at the periphery in six eyes and juxtapapillary in three eyes. At the initial examination lesion area was observed as an area with a decreased flow signal on SS-OCTA.There was perilesional capillary disruption in superficial and deep capillary plexi together with a diffuse capillary network attenuation and non-detectable flow signal zones in the choriocapillaris slabs. In addition to sulfamethoxazole-trimethoprim and azithromycine combination oral corticosteroids were only co-administered in five (35%) eyes with macular involvement. The chorioretinal scar formation was observed in four to 16 weeks. At the time of inactivity, original lesion was diminished in size when compared to its baseline in all study eyes (p = 0.001) with a mean black pixel reduction percentage of 21.8%. The reduction was 15.4% in eyes with macular lesion, 31.6% with peripheral lesions and 18.1% with juxtapapillary lesions (p = 0.001, p = 0.032, p = 0.028, p = 0.043, respectively). Visual acuity was correlated with black pixel reduction percentage in eyes with macular lesion (r = 0.56, p < 0.001). Conclusion Active toxoplasma retinochoroiditis lesion size diminished with the healing process as expected and this could be monitorized with an OCTA based image analysis technique. Macular lesions showed less reduction in lesion size despite the addition of oral corticosteroids in contrast to peripheral and juxtapapillary lesions.

Utilization and Energy-Saving Analysis of Inkjet and Laser Printed Eco-Hollow Embedded Fonts: A Comparison of English and Thai Alphabets

The utilization of eco-fonts for office printing is a sustainable, &ldquo;green&rdquo; printing concept, which has obvious economic benefits. As a result, it has a significant effect on environmental sustainability. This practice's fundamental problem is the decreased quality of text printed using eco-fonts compared to those printed with regular fonts. The aim of this research is eco-font efficiency estimation, i.e. determination of toner usage reduction level of inkjet-printed documents typed with this font type, as well as estimation of the extent humans perceive differences between text printed with eco-font and the one printed by its &ldquo;non-eco&ldquo; equivalent. Combining the instrumental measuring method and digital image analysis, it was found that this simple principle (eco-font utilization) enables substantial toner usage reduction for an inkjet printing system. At the same time, a visual test showed that the visual experience of text printed using eco-font was sufficient. In addition, awareness of the benefits that eco-font utilization brings, change users&rsquo; attitude towards eco-font quality. The concept of removing the black pixel from this commonly used Thai font has a great potential for the sustainability printing process, and this simple solution could be applied to other languages as part of the GIT campaign.

Side-Chain Polyimides as Binder Polymers for Photolithographic Patterning of a Black Pixel Define Layer for Organic Light Emitting Diode

A pixel define layer (PDL) in an organic light emitting diode (OLED) is patterned using a photolithographic process before the deposition of organic layers on top of ITO anode. If the patterning of PDL on OLED panels can be achieved using a black photoresist, the patterning of black matrix (BM) on top of PDL patterns can be omitted by reducing the reflection of ambient light from OLED panels. In this study, we synthesized a series of side-chain-type polyimides as binder polymers of black photoresists and investigated the potential of using the black photoresist for the fine patterning of black PDL on OLED panels.

Tolerance Control Using Subvoxel Gray-Scale DLP 3D Printing

3D printing manufacturing technology has been utilized in various applications due to its promising manufacturing advantages. Desktop Digital Light Processing (DLP) printers provide high-resolution products with a moderate price range. DLP uses an array of micromirrors to transmit UV light from the light projector in order to perform selective curing of a prepolymer resin and turn it in to the required geometry. The CAD file is transformed into several slices according to the layer thickness. Each slice is then converted to an image of black and white pixels, in which each white pixel actuates a corresponding micromirror to transmit the UV light to cure a corresponding voxel, while a black pixel corresponds to no actuation, which means no curing for the corresponding voxel. The micromirror’s size determines the resolution of the printer. Although a theoretical voxel size can be determined as a function of the micromirror’s dimensions and layer thickness, the actual voxel volume depends on several parameters such as the layer thickness, UV exposure time, and UV exposure intensity. Controlling these three parameters would result in more accurate 3D printed parts and more control over the dimensional tolerance. In this paper, the effect of variable light intensity in terms of grayscale pixels is studied along with the exposure time and layer thickness to manipulate the voxel horizontal dimensions. This enables printing with voxel dimensions below the size of the micromirrors in the DLP, which improve the geometric dimensioning and tolerance of the printed parts.

FUSION OF LIDAR DATA AND MULTISPECTRAL IMAGERY FOR EFFECTIVE BUILDING DETECTION BASED ON GRAPH AND CONNECTED COMPONENT ANALYSIS

Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building’s occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets: Aitkenvale and Hervey Bay, for object-based and pixel-based completeness, correctness, and quality. The proposed technique detects buildings larger than 50 m² and 10 m² in the Aitkenvale site with 100% and 91% accuracy, respectively, while in the Hervey Bay site it performs better with 100% accuracy for buildings larger than 10 m² in area.