Background Medical image segmentation plays an important role in assisting clinical diagnosis, as well as medical education to enhance learning anatomy and pathology. A 3D anatomical model which can be either visualised as 3D reconstruction or virtual reality views or 3D printed models adds valuable information to standard 2D visualisations for assessing the depth of the abdominal region structures and abnormalities and enhancing the learning experience. Aim. This study aims to explore the methodology and efficiency for 3D segmentation of abdominal organs comparing the abdominal region of the normal human anatomy intestinal using an open source software 3D Slicer. Methods Two CT scans of anonymised images with normal and intestinal enteritis were selected to be segmented, analysed, and converted into 3D virtual anatomical models. The models were used in comparison to assess limited areas that could not be assessed via 2D visualisation and depict differences from the soft tissue organs. Results The majority of the organs were able to be image processed and converted into 3D visualisation. Evidently, the gastrointestinal system poses varying challenges due to irregular pathway and difficulties to distinguished density value towards adjacent organs. Despite the challenge, 3D segmentation of the small and large intestines were visualised and differentiated. Conclusion This study demonstrates the feasibility of utilising 3D slicer for multi-organ segmentations, although it still poses many challenges and limits to soft tissue components. Further development of automatic segmentation is necessary to make the image processing and segmentation approach more practical for routine applications.