Download 3-D Imaging Technologies in Facial Plastic Surgery, an Issue by John Pallanch PDF

By John Pallanch

A international pool of surgeons and researchers utilizing three-d imaging for facial cosmetic surgery current issues on: snapshot fusion in pre-operative making plans; using 3D imaging instruments together with stereolithographic modeling and intraoperative navigation for maxillo-mandibular and intricate orbital reconstruction; customized, three-d, intraoperative surgical courses for nasal reconstruction; the advantages and bounds of utilizing an built-in 3D digital procedure for maxillofacial surgical procedure; 3D quantity evaluation options and computer-aided layout and production for pre-operative fabrication of implants in head and neck reconstruction; A comparability of other new 3D imaging applied sciences in facial cosmetic surgery; 3-D images within the target research of quantity augmentation together with fats augmentation and dermal fillers; evaluate of alternative rhinoplasty innovations through overlay of prior to and after 3D photographs; 3D volumetric research of mixed facial lifting and volumizing...

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Predictive algorithms are used to extrapolate the influence of growth, surgery, or interceptive treatment on an existing osseous platform based on normative estimates. They provide an end-point estimate of the final result but have no foundation for accuracy. The use of this term in 3D imaging is inaccurate because it implies an assurance on the expected outcome (almost a guarantee on the virtual outcome), a result that a patient might believe is always achievable. 3. Simulation. 50-55 Computer-based simulation gives the clinician the opportunity to perform virtual surgery or treatment, increasing the possibility of a successful outcome with no risk to the patient.

At the center of this approach is the true digital patient or “patient-specific anatomic reconstruction” (PSAR). The PSAR is not just a series of 3D images or traditional photographs/radiographs available in a file to view separately, it is an anatomically accurate record in which all of the patient’s 3D images (ie, CT/CBCT, MRI, facial surface images, teeth and so forth) are superimposed into 1 valid 3D structure and combined with the relevant biomechanical properties. This process, resulting in a single dataset from the combination of relevant information from 2 or more independent datasets, is called image fusion.

With the surface errors that are typical with CBCT (eg, chin restraint, motion artifacts, soft tissue draping), a visual inspection of the image is recommended so the clinician can select the best regions on the face for registration. For example, the clinician would not select the region around the chin if there is a restraint. Depending on the individual DICOM skin, users typically do not select regions of the face that are subject to positional change from one modality to another, such as the mandible or the eyes.

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