METHODS: An online cross-sectional survey was conducted among final year students in medical imaging programs from six institutions in Malaysia. Purposive convenience sampling has been employed. Data collection was related to students' interest in postgraduate study and possible factors that may affect students' intention to pursue postgraduate education after study degree completion. The questionnaire was a combination of a Likert Scale and open-ended question.
RESULTS: A total of 148 (female, n = 132 and male, n = 16) responses were included in the analysis. Among the participants, n = 93 (62.8 %) of students intended to pursue study. The highest choice of study was mixed mode (41.9 %) and cardiac imaging was the field of choice by the students (22.3 %). Five factors have been found to significantly correlate with the students' intention to pursue postgraduate study in medical imaging which were student attributes, being an academician, remuneration, finance, and social influences (p 0.05).
CONCLUSION: Five out of seven factors tested were found to significantly influence students' decision to pursue postgraduate education in medical imaging. Effective strategies based on the influencing factors should be strategized to encourage more students to pursue postgraduate education in medical imaging.
IMPLICATIONS FOR PRACTICE: Implementation of effective strategies based on the influencing factors will improve access to education among radiography students, ultimately enhancing future radiographers' capability and competency.
MATERIALS AND METHODS: The panoramic radiographic images belonging to children with special needs from the two teaching dental hospitals in Malaysia aged between 5 and 16 years were included in the study. The evaluation was performed by two observers using three methods (London Atlas, Demirjian, and Willems methods) to estimate the accurate DA. The outcome was determined by comparing the mean of the DA and CA.
RESULTS: A total of 52 panoramic radiographs were available for the analysis. The London Atlas and Demirjian methods overestimated the DA with a mean of 0.05 and 0.20 years, respectively, while the Willems method underestimated by 0.19 years. The London Atlas method was highly precise and accurate, while Demirjian and Willems methods were the least precise and accurate.
CONCLUSION: The London Atlas method of DA estimation is highly accurate and valid for children with special needs in the Malaysian population, followed by the Willems and Demirjian methods.
METHODS: We proposed a new feature extraction method by replacing fully-connected layer with global average pooling (GAP) layer. A comparative analysis was conducted to compare the efficacy of 16 different convolutional neural network (CNN) feature extractors and three machine learning classifiers.
RESULTS: Experimental results revealed the potential of CNN feature extractors in conducting multitask diagnosis. Optimal model consisted of VGG16-GAP feature extractor and KNN classifier. This model not only outperformed the other tested models, it also outperformed the state-of-art methods with higher balanced accuracy, higher Cohen's kappa, higher F1, and lower mean squared error (MSE) in seven OA features prediction.
CONCLUSIONS: The proposed model demonstrates pain prediction on plain radiographs, as well as eight OA-related bony features. Future work should focus on exploring additional potential radiological manifestations of OA and their relation to therapeutic interventions.
METHODS: A ball phantom was scanned using panoramic mode of the Planmeca ProMax 3D Mid CBCT unit (Planmeca, Helsinki, Finland) with standard exposure settings used in clinical practice (60 kV, 2 mA, and maximum FOV). An automated calculator algorithm was developed in MATLAB platform. Two parameters associated with panoramic image distortion such as balls diameter and distance between middle and tenth balls were measured. These automated measurements were compared with manual measurement using the Planmeca Romexis and ImageJ software.
RESULTS: The findings showed smaller deviation in distance difference measurements by proposed automated calculator (ranged 3.83 mm) as compared to manual measurements (ranged 5.00 for Romexis and 5.12 mm for ImageJ software). There was a significant difference (p