Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2024/r/gumushane/12537
  3D reconstruction of foot metatarsal bones of women using CT images

  Reis, Hatice Çatal

  Bone morphology is a fundamental factor in human anatomy. However, foot and ankle bones have yet to be adequately evaluated in 3-dimensional. It is essential to present the biometric data of anatomical structures. This study formed 3D models of the metatarsal bones of the feet of young women using image processing techniques to examine biometric measurements and determine morphology on these 3D models. This study investigated bone lengths in the metatarsal bones of women feet in Türkiye. A total of ten young female subjects were included as the test group to measure the lengths of their foot metatarsal bones using CT (Computed Tomography) scans, and 20 feet (left/right) were examined. The parameters that were used for the analyses were detector collimation of 64x0.5 mm, section thickness of 0.5 mm, current of 100 mA, tube voltage of 120 kVp, and pixel spacing of 512x512 pixels with a monochrome resolution providing 16-bit gray levels. CT images were processed, and a 3D metatarsal reconstruction was gathered. Then, the biometric measurements were calculated on this 3D model. For the lengths of the volunteers' right/left foot metatarsal bones, statistically significant differences were calculated using a one-sample t-test. For the female metatarsal bones of the left and right feet, statistically significant differences in length were calculated on 3D models. The mean results of the metatarsal length measurements were MT1(metatarsal): 59.52±1.42 mm, MT2: 70.45±1.82 mm, MT3: 66.25±1.82 mm, MT4: 65.12±1.81 mm and MT5: 63.63±1.81 mm. The level of statistical significance was accepted as p <0.05 for the one-sample t-test conducted for each metatarsal bone. The lengths of the right foot metatarsal bones were different from those of the left foot metatarsal bones in the sample. However, this difference was approximately one-tenth of a millimeter. The shortest bone was MT1, and the longest bone was MT2. These measurements are consistent with the anatomical information in the literature. The 3D models from the CT images and the biometric measurements of the metatarsal bones were found to be reliable and accurate.

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  İncele
• MakaleAçık Erişim2023/r/gumushane/14417
  Effect of denoising methods for hyperspectral images classification: DnCNN, NGM, CSF, BM3D and Wiener

  Günen, Mehmet Akif; Besdok, Erkan

  Hyperspectral images are widely used for land use/cover analysis in remote sensing due to their rich spectral information. However, these data often suffer from noise caused by various factors such as random and systematic errors, making them less useful for end-users. In this study, denoising methods (i.e., DnCNN, NGM, CSF, BM3D, and Wiener) for hyperspectral images were compared using the Pavia University hyperspectral dataset with four different noise types: Gaussian, Salt & Pepper, Poisson, and Speckle. After denoising, the k-nearest neighbor method was used to classify the image, and statistical and visual performance comparisons were performed on the classified data. Six performance metrics-Accuracy, Sensitivity, Specificity, Precision, F-Score, and G-Mean-were employed to compare the outcomes qualitatively. The findings demonstrate that DnCNN and BM3D have the best outcome performance for all four noise types. Due to their lack of sensitivity and specificity, the CSF and Wiener approaches had low performance for particular noise sources. For all noise types, the NGM approach had the worst results. The validated instruments not provide effective results when it came to denoising Salt & Pepper noise, but they managed to produce outstanding results when it came to denoising Poisson noise. In order to enhance the quality and usability of hyperspectral images for land use/cover analysis, this study emphasizes the significance of choosing an effective denoising technique.

  İncele
• MakaleAçık Erişim2023/r/gumushane/12780
  Detection of COVID-19 infection from CT images using the medical photogrammetry technique

  Çatal Reis, Hatice; Türk, Veysel; Kaya, Serhat

  Medical data such as computed tomography (CT), magnetic resonance imaging (MRI), and Ultrasound images are used in medical photogrammetry. CT images have been used frequently in recent years for the diagnosis of COVID-19 disease, which has contagious and fatal symptoms. CT is an effective method for early detection of lung anomalies due to COVID-19 infection. Machine learning (ML) techniques can be used to detect and diagnose medical diseases. In particular, classification methods are applied for disease diagnosis and diagnosis. This study proposes traditional machine learning algorithms Random Forest, Logistic Regression, K-Nearest Neighbor and Naive Bayes, and an ensemble learning model to detect COVID-19 anomalies using CT images. According to the experimental findings, the proposed ensemble learning model produced an accuracy of 96.71%. This study can help identify the fastest and most accurate algorithm that predicts CT images with Covid-19 during the epidemic process. In addition, machine learning-based approaches can support healthcare professionals and radiologists in the diagnostic phase.

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  İncele
• MakaleAçık Erişim2023/r/gumushane/11921
  Investigation of geometric object and indoor mapping capacity of Apple iPhone 12 Pro LiDAR

  Günen, Mehmet Akif; Erkan, İlker; Aliyazıcıoğlu, Şener; Kumaş, Cavit

  LiDAR (light detection and ranging) sensors use laser beams to calculate distances in the surroundings. These sensors can be applied to a wide range of tasks, and they are frequently helpful in tasks like building 3D maps, navigating airplanes, robots, conducting mining operations, and automated driving. High-resolution distance measurements are taken by LiDAR sensors, but they also gather environmental data. This information aids in locating, identifying, and quantifying things and their surroundings. The iPhone 12 Pro, which Apple released in 2020, was evaluated for accuracy with various geometric shapes and its capacity to recognize indoor environments. Free of charge 3D Scanner and the Clirio Scan application were employed in this situation. However, it was found that the root mean square error and mean error in indoor mapping were ±1.41 cm and-0.56 cm in 3D Scanner and ±3.94 cm and-0.60 cm in the Clirio Scan application, respectively, despite the findings obtained showing low accuracy in scanning small geometric objects due to the scanning difficulty. Clirio does not reject the null hypothesis in the t-test that was conducted. The accuracy of the LiDAR sensor in indoor mapping has been shown to be more promising than that of small items. In order to evaluate the reliability and reusability of the indoor mapping application according to reference measurements, intraclass correlation test was performed and the results were determined to be reliable.

  İncele
• MakaleYalnız künye2020/r/gumushane/14890
  Light rail line design for East Black Sea region: A case study of Trabzon

  Reis, Hatice Catal; Birinci, Abdulkadir

  Growing cities need to improve transportation in response to the accessibility needs of ever-expanding urban and metropolitan populations. Metropolitan Municipalities have to find low-cost, nature friendly, bus/train/subway transfer, and socially responsible transportation solutions that can meet the accessibility needs of urban residents and assist future economic development in urban areas. In this study, the light rail network was designed for the province of Trabzon by using orthophoto and Landsat satellite images. While this light rail network is being constructed, many criteria such as regional population density, slope, minimum service interval, integration with other transportation networks, geological structure, and proximity to public institutions and organizations have been used together. These criteria are shown with a GIS-based design model. Analysis maps were created by using the conditions/criteria and synthesis maps used in the design model. The 102 km route features 205 stops, extending from Of along to Besikduzu. A combined bus and light rail network will significantly improve public transport access to major public institutions and organizations, sporting and entertainment facilities, universities, schools, health precincts, bazaars, shopping malls. It is foreseen that the light rail system will provide the most suitable, modern, fast, comfortable and safe transportation in the long term considering the number of passengers and many other criteria. This light rail system designed for the province of Trabzon is thought to be a pioneering work for the Black Sea region through the interpretation of the resulting map and route networks.

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