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Assessment of Students’ Ability to Identify Anatomical Structures on Computed Tomography Images

Abstract

The study assesses students’ ability to identify anatomical structures on computed tomography images. Computed tomography provides sectional representations of internal anatomical structures and is an important imaging modality for understanding the spatial arrangement of tissues within the human body. The ability to recognize anatomical structures on computed tomography images is an important component of radiological anatomy education and may help students connect conventional anatomical knowledge with clinical imaging. The study will assess students’ ability to identify selected anatomical structures on computed tomography images. The specific objectives will include determining students’ accuracy in identifying structures on CT images, assessing their ability to recognize structures at different sectional levels and anatomical regions, evaluating their understanding of the relationships between structures visible on CT images, and identifying structures or image presentations that students find more difficult to interpret. A cross-sectional descriptive research design will be adopted for the study. Undergraduate students who have received relevant anatomy and basic radiological anatomy instruction will be selected using an appropriate sampling technique. Data will be collected through a standardized practical assessment involving appropriately selected and labelled computed tomography images from relevant anatomical regions. Students’ responses will be scored using a predetermined marking scheme, and the data will be analyzed using descriptive statistics such as frequency, percentage, mean, and standard deviation, with appropriate inferential tests applied where necessary. The study is expected to reveal varying levels of ability to identify anatomical structures on computed tomography images. Students may demonstrate stronger performance when recognizing large and distinctive structures, while greater difficulties may be observed with small structures, closely related tissues, structures with similar appearances, and images obtained at unfamiliar sectional levels. Variations may also occur in students’ ability to interpret spatial relationships and relate CT appearances to conventional three-dimensional anatomical knowledge. The findings will be useful to anatomists, anatomy educators, radiologists, medical educators, and curriculum developers by providing information on students’ ability to apply anatomical knowledge to CT-based imaging. The study may help identify areas where additional exposure to CT images, guided image interpretation, sectional anatomy exercises, three-dimensional models, and radiological demonstrations may be beneficial. It may also support the integration of clinically relevant imaging resources into undergraduate anatomy teaching and practical assessment. The study will conclude by assessing students’ ability to identify anatomical structures on computed tomography images and documenting areas of relative strength and difficulty. It is recommended that anatomy education should provide regular opportunities for students to interpret CT images and relate sectional appearances to three-dimensional anatomical structures. Further studies involving larger and more diverse student populations and different radiological anatomy learning environments are also recommended.

Keywords: Computed tomography, CT images, anatomical identification, radiological anatomy, anatomy education, undergraduate students, anatomical structures, sectional anatomy, anatomical orientation, spatial relationships, medical imaging, anatomy assessment, practical anatomy, clinical anatomy, imaging-based learning.