@article{verykokou2023overview,

title = {An Overview on Image-Based and Scanner-Based 3D Modeling Technologies},

author = {Styliani Verykokou and Charalabos Ioannidis},

url = {https://www.mdpi.com/1424-8220/23/2/596},

doi = {10.3390/s23020596},

issn = {1424-8220},

year  = {2023},

date = {2023-01-04},

urldate = {2023-01-04},

journal = {Sensors},

volume = {23},

number = {2},

pages = {596},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Advances in the scientific fields of photogrammetry and computer vision have led to the development of automated multi-image methods that solve the problem of 3D reconstruction. Simultaneously, 3D scanners have become a common source of data acquisition for 3D modeling of real objects/scenes/human bodies. This article presents a comprehensive overview of different 3D modeling technologies that may be used to generate 3D reconstructions of outer or inner surfaces of different kinds of targets. In this context, it covers the topics of 3D modeling using images via different methods, it provides a detailed classification of 3D scanners by additionally presenting the basic operating principles of each type of scanner, and it discusses the problem of generating 3D models from scans. Finally, it outlines some applications of 3D modeling, beyond well-established topographic ones.},

keywords = {3D modeling, CBCT, CMM, CT, laser scanners, MRI, multi-view stereo, scanners, segmentation, structure from motion},

pubstate = {published},

tppubtype = {article}

}

@article{verykokou2022evaluation,

title = {Evaluation of 3D Modeling Workflows Using Dental CBCT Data for Periodontal Regenerative Treatment},

author = {Styliani Verykokou and Charalabos Ioannidis and Christos Angelopoulos},

url = {https://www.mdpi.com/2075-4426/12/9/1355},

doi = {10.3390/jpm12091355},

issn = {2075-4426},

year  = {2022},

date = {2022-08-23},

urldate = {2022-08-23},

journal = {J. Pers. Med.},

volume = {12},

number = {9},

pages = {1355},

publisher = {MDPI},

abstract = {The cone beam computed tomography (CBCT) technology is nowadays widely used in the field of dentistry and its use in the treatment of periodontal diseases has already been tackled in the international literature. At the same time, advanced segmentation methods have been introduced in state-of-the-art medical imaging software and well-established automated techniques for 3D mesh cleaning are available in 3D model editing software. However, except for the application of simple thresholding approaches for the purposes of 3D modeling of the oral cavity using CBCT data for dental applications, which does not yield accurate results, the research that has been conducted using more specialized semi-automated thresholding in dental CBCT images using existing software packages is limited. This article aims to fill the gap in the state-of-the-art research concerning the usage of CBCT data for 3D modeling of the hard tissues of the oral cavity of patients with periodontitis using existing software tools, for the needs of designing and printing 3D scaffolds for periodontal regeneration. In this context, segmentation and 3D modeling workflows using dental CBCT data that belong to a patient with periodontitis are evaluated, comparisons between the 3D models of the teeth and the alveolar bone generated through the experiments that yielded the most satisfactory results are made, and an optimal and efficient methodology for creating 3D models of teeth and alveolar bone, especially for being used as the basis for generating bioabsorbable 3D printed scaffolds of personalized treatment against periodontitis, is discussed.},

keywords = {3D modeling, CBCT, cone beam computed tomography, dental applications, periodontal treatment, periodontitis, scaffold, segmentation},

pubstate = {published},

tppubtype = {article}

}