Comparison of Three 3D Segmentation Software Tools for Hip Surgical Planning

Abstract

In hip arthroplasty, preoperative planning is fundamental to reaching a successful surgery. Nowadays, several software tools for computed tomography (CT) image processing are available. However, research studies comparing segmentation tools for hip surgery planning for patients affected by osteoarthritic diseases or osteoporotic fractures are still lacking. The present work compares three different software from the geometric, dimensional, and usability perspectives to identify the best three-dimensional (3D) modelling tool for the reconstruction of pathological femoral heads. Syngo.via Frontier (by Siemens Healthcare) is a medical image reading and post-processing software that allows low-skilled operators to produce prototypes. Materialise (by Mimics) is a commercial medical modelling software. 3D Slicer (by slicer.org) is an open-source development platform used in medical and biomedical fields. The 3D models reconstructed starting from the in vivo CT images of the pathological femoral head are compared with the geometries obtained from the laser scan of the in vitro bony specimens. The results show that Mimics and 3D Slicer are better for dimensional and geometric accuracy in the 3D reconstruction, while syngo.via Frontier is the easiest to use in the hospital setting.

A virtual biopsy study of microsatellite instability in gastric cancer based on deep learning radiomics

“…Additionally, accurate and efficient tumor region segmentation methods are important to ensure the quality of quantitative image features. It has been confirmed that 3D Slicer has better segmentation algorithms and higher segmentation accuracy than other image segmentation software while being more accessible as free open-source software [ 42 ]. Moreover, the radiomics features extracted after image segmentation using 3D Slicer have higher robustness and are, therefore, recommended for use in high-throughput data mining efforts for medical oncology imaging [ 43 ].…”

Physiological Offset Parameters of the Adult Shoulder Joint—A MRI Study of 800 Patients

“…In order to finally clarify this question, additional studies that specifically examine the HO, GO and LGHO between left- and right-handers are needed. The clinical consequence of these results are that, in contrast to the hip joint [ 26 , 27 ], for the surgical treatment of severe degenerative diseases or fractures in the shoulder joint, the healthy contralateral side cannot be used uncritically for planning the offset reconstruction. This hypothesis must be supported by further studies.…”

Carpal kinematics and morphological correlates of wrist ulnar deviation mobility in nonhuman anthropoid primates

“…In our protocol, the CT scan of each specimen was segmented via a semi‐automated approach using the region growing function to produce individual masks of each bone, which were then output as 3D polygon models using the “Optimal” setting in the STL+ module in Mimics 11.11 or 19.0. Using the Mimics algorithms to produce 3D models has high geometrical accuracy even in areas such as the articulated hip joint, which is difficult to segment without significant manual editing of masks and has been shown to have dimensional accuracy of 0.353 mm (Mandolini et al, 2022). Although minor differences in minimum thresholding values among specimens were required to produce solid models (450–740 HU) in the current study, the bones examined were typically loose packed in the neutral position and therefore easily separated without consequential manual editing of masks.…”