Sürdürülebilir Kalkınma Amaçları
Yazarlar
Yayınlar
- MakaleAçık Erişim2024Scopus SJRQ33D 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.
AtıfScopus1OpenAlex1
İncele - MakaleAçık Erişim2023Detection 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.
- MakaleAçık Erişim2018Detection of foot bone anomaly using medical photogrammetry
Reis, Catal H.
Photogrammetry has been used for medical diagnostic and treatment. Mostly used medical photogrammetric techniques are Ultrasound, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) images. CT and MRI are the most effective method for the early detection of foot and ankle anomaly. Researchers have been developing various methods to detect anomaly. Many image segmentation techniques are available in the literature. Computer Aided Diagnosing (CAD) system has been proposed in this study for detection of foot bone anomaly by the analysis of CT images. In this study, a segmentation based on edge detection method is proposed for the classification of anomaly in foot CT images. Edge detection algorithms are the most commonly used techniques in image processing for edge detection. Canny edge detector is evaluated in this study. In this study, .dicom medical image standard format and ten male patient's foot CT images (245 images and 50 test data) are used. The used parameters are detector collimation of 64 mm, scanning thickness of 1-5 mm, and pixel sizes of 512x512 in radiometric resolution of 16 bits' gray levels. The proposed method consists of five major steps: (i) calculating the horizontal & vertical gradient, (ii) determining gradient magnitude and gradient direction, (iii) applying non-maximal suppression, (iv) computing high and low thresholds, (v) hysteresis thresholding are applied to the multi-detector computed tomography to detect the bone anomaly. In this study, automatic edge-based digital image processing techniques are applied to detect of foot bone anomaly. The proposed canny segmentation method enables users segment anomaly in MDCT of foot very quickly and efficiently. The results demonstrate that the proposed segmentation method is effective for segmenting anomaly. The proposed method obtains satisfactory performances in terms of accuracy and F-measure the area under Receiver Operating Characteristic curve (ROC curve (AUC)). The proposed segmentation method achieves an accuracy of 0.86 and F-measure of 0.92, respectively. The purpose of our study is to detect the anomaly of the foot and it was the simplest and less time consuming process.
AtıfWoS4TR Dizin2
İncele - BildiriYalnız künye2013Three-dimensional modeling of women's talus bone
Catal, Hatice; Corumluoglu, Ozsen; Bayram, Bulent
In this study, semi-automatic region-based digital image processing techniques were used to create 3-dimensional (3D) virtual model of talus bone. 5 ballerinas and 5 sedentary women have voluntarily been involved in to the study. Total 20 right and left feet have been used which have been taken from the multidetector computed tomography (MDCT). We used 3D Doctor Software in this research. Image preprocessing, segmentation and 3D modeling steps were done respectively. Volume, area and length based various statistical ratios were computed according to the measurements. The comparisons have been accomplished by using these ratios for sedentary and ballerinas. As an outcome, some differences were found in talus of ballerina and sedentary women. We hope that the results from the biometric and reconstructive techniques carried out in this study will contribute to the present knowledge in orthopedics and digital image processing in this area.
- BildiriYalnız künye2012Using 3D models from multidetector computed tomography images for diagnostic of Hallux-valgus
Catal, Hatice; Corumluoglu, Ozsen
Medical image processing techniques is often used in medicine or some engineering fields. In this study, we used basic techniques of metric digital image processing. Axial MDCT (Multidetector Computed Tomography) Ballerina's feet images were used to form 3D models by 3D-Doctor software. The virtual 3D models are in high accuracy. Hallux-valgus angles were calculated and recorded by using these 3D virtual models. We hope that the results from the biometric and reconstructive techniques carried out in this work will contribute to the present knowledge in medicine especially on ballerina's foot health and digital image processing in this area.
AtıfScopus1İncele