DEPARTMENT OF MEDICAL RADIOGRAPHY

In this study, we compared manual and automated segmentation algorithms in Computed Tomography (CT) imaging of the liver. Segmentation is the delineation of anatomical structures on a CT/MRI image for treatment and dose planning purposes. Accuracy in the segmentation of organs in CT imaging is a critical step in diagnosis and therapy planning. Normally, manual segmentation performed by trained practitioners is the gold standard for the delineation of these anatomical structures. However, manual segmentation is time-consuming, subject to interobserver differences, and also needs a level of expertise (Lee et al., 2024). Automated segmentation on the other hand, is a potential solution to the problems faced due to manual segmentation, despite this development, there is still an ongoing debate questioning the accuracy and reliability of automated segmentation due to little knowledge about its capabilities (Raudaschl et al., 2017). The main objectives of this study are to compare the accuracy and segmentation time of manual and automated segmentation, also to assess the inter-observer variability between 10 different observers. This study was carried out at the University of Benin Teaching Hospital (UBTH) using an anonymized CT dataset segmented manually using 3D-slicer and automatically using TotalSegmentator. A quantitative analysis of 100 segmentation masks produced by the segmentation of 10 anonymized CT images of patients by 10 observers (radiographers and radiotherapists) was conducted to evaluate the accuracy, time efficiency of automated algorithms and inter-observer variability of manual segmentation. The accuracy of automated segmentation was measured using the mean Dice Similarity Coefficient value, speed of both types of segmentation compared was measured using time and the inter-observer variability was measured using the Inter Class Correlation and Fleiss’ Kappa. The results obtained indicates that automated segmentation is as accurate as manual segmentation with a mean DSC value of 0.85±0.03 and also more time efficient with a 65% decrease in the segmentation time per image. This study also shows that the manual segmentations done by different observers are not far off from each other proving how reproducible it is. The Inter Class Correlation and Fleiss' Kappa was used to determine this with their score being 0.720 and 0.683 respectively. This indicates a moderate to strong agreement between segmentation done by different observers and if there is a strong agreement, the variability will be minimal. The DSC gotten is also greater than 0.7, giving a confirmation of how accurate
automated segmentation is. From the results above, it was concluded that automated segmentation is as accurate and faster than manual segmentation. It was also concluded that there are minimal differences between segmentations done by different observers. A wide clinical adoption, Training of radiographers, educational inclusion and further research is recommended to increase the awareness and integration of automated segmentation in various clinical systems.

Background: Industrial radiography is a crucial non-destructive testing method that ensures the safety and integrity of industrial infrastructure. Despite its importance, awareness and adoption of industrial radiography as a career path among radiography students remain underexplored, particularly in Nigeria. Aim: This study investigates the awareness of industrial radiography among radiography students at the University of Benin, Nigeria. It examines their awareness levels, sources of information, attractors, detractors, and perceptions of industrial radiography as a career option. Method: A cross-sectional survey design was used, a self constructed questionnaire was used in collecting data from 266 radiography students. Descriptive statistics and chi-square tests were applied to analyze the data, assessing relationships between awareness and various demographic and academic factors. Results: 69.5% of students were aware of industrial radiography, with media (38.4%) and lectures (32.4%) being the primary sources of information. - 79.7% believed industrial radiography was not adequately covered in their curriculum. The key attractors to the field were the opportunity to work in an industry (29.3%) and improved remuneration (29.3%), while the main detractors were a preference for medical radiography (30.1%) and fear of radiation hazards (25.6%). Despite 82.3% perceiving industrial radiography as a prestigious career, 89.1% felt it was not a popular career choice in Nigeria. - Chi-square tests showed a significant relationship between age group and awareness (p = 0.004) and between awareness of industrial radiography as a career and general awareness (p < 0.001). xi No significant relationships were found between gender, level of study, curriculum coverage, or perception of prestige and awareness levels. Conclusion: While awareness of industrial radiography is relatively high, significant gaps exist in curriculum coverage and practical training. The study recommends integrating industrial radiography into the curriculum, fostering university-industry collaborations, and conducting awareness campaigns to promote industrial radiography as a viable career option. These steps are essential for developing a skilled rkforce to enhance the safety and integrity of Nigeria's industrial infrastructure.

Topic: Occupational Stress Among Radiographers: A Comparative Analysis between Public and Private Clinical Settings. Background of the Study: Occupational Stress is a critical issue affecting healthcare professionals including radiographers which has high tendencies of impacting their wellbeing as well overall working efficiency. While stress is prevalent among radiographers, it is imperative to determine which specific setting it remains prevalent in as well as steps to
mitigate it. Objective of the Study: This study is aimed at analyzing the stress levels between radiographers working in the private and public clinical settings. Methods/Materials: A cross-sectional survey design was adopted involving sixty (60) radiographers in various public and private centers in Benin City. Data was collected using a well-structured self-administered questionnaire and analyzed with the Statistical Package for Social Sciences version 25. Results/Findings: The results revealed that there was a significantly higher stress levelsamong radiographers in the private setting than in the public setting. Conclusion: From this study, it can be concluded that the type of clinical setting is a determinant factor for measuring occupational stress among radiographers in Benin City, Edo state.