3D Scanning Technology

Premier Cosmetic Medical Clinic, Adelaide South Australia

3D technology

epiclinic® is the global pioneer of the SAFV Scan imaging system.

Dr Michael Molton of epiclinic® has invented the revolutionary imaging system with international professional scientists and the Australian University team. Working with a team of UWA scientists as Linkage project with Australian Research Council

When it comes to recording the results of your treatments at epiclinic® Dr Molton uses a system much more informative than traditional photos. Traditional photos were leading technology to track treatment process when the focus of treatment was solely on filling in lines and wrinkles. However, with changes and improvements to the way we treat the signs of aging, the recording of treatment results has adapted too.

3D imaging with the SAFV scanning system creates a three-dimensional view of the treatment area as opposed to the two-dimensional view offered by traditional cameras. This means not only are we treating your symptoms in a more advanced manner, we can be sure of your results, as the SAFV system shows the angles and contours of your treatment area.

Information for Doctors and Cosmetic Medicine Practitioners

SAFV Scanning, leading the end of the use of cameras in Cosmetic Medicine?

Even though cosmetic medical practice has been around for decades, many doctors continue to ‘record’ results with the camera. Standardised photography and digital photography may have improved the quality of the photos, but the reliance on 2D photographs continues as the primary record of treatment.

Most other medical fields have developed sophisticated imaging like CT, MRI, ULTRASOUND, PET, and even earlier, X-ray. The primary reason for not using these technologies in Cosmetic Medicine is invasiveness and in many cases the cost of such devices is not warranted in elective procedures that are aimed at improving quality of life (QOL) and self-esteem.

This paradigm shift of replacing lost volume and the virtual abandonment of chasing lines and wrinkles has simply not been extrapolated to thinking about how we assess the three-dimensional outcome.

When we were all injecting lines and wrinkles, photographs were probably satisfactory. After all, we were recording a two dimensional treatment with two dimensional photography.

Injecting volume is not two dimensional. It is three. As CMPs we need to get this volume in the right place with the correct contours, and the patient needs to understand how the volume changes that occur with aging can be replenished, with what, and by how much.

It makes perfect sense to record three dimensional volume changes, with three dimensional imaging, not two dimensional photos. It would be better still if we can actually predict and quantitatively measure the 3D changes and view them from infinite angles. With SAFV scanning (statistical analysis of facial volume) this manoeuvre is performed simply by rotation of the 3D image or scan through X, Y, and Z axes.

Another inescapable fact is that the principle of quality assurance in medicine has become more important than ever before so we should be paying far more attention to quantitative results. Everybody else has and with SAFV scanning we should too.

The credibility of evidence-based medicine, collaborative initiatives and accreditation are now standard in all facets of medicine. It is no longer enough to show the-best-of before and afters where the lighting, patient expression, exposure time and depth of field provide an apparently improved effect as a result of treatment. Of course, you never see the average or poor outcomes.

How does SAFV scanning work?

SAFV scanning determines quantitative values of volume changes and how they affect physical appearance of the face in ways we actually see them with our own stereo vision. This technology employs the matching of stereo-video micropolygons just like we do ourselves with our own built-in 3D interpretation of our world when ‘scanning’ through pieces of a jigsaw puzzle to find the part with the best fit. SAFV involves over-laying before and after 3D scans of the patient’s face by working out which micropolygons are related and then produces a single statistical-plus-visual 3D image of the changes you just made with your work. It shows your high points, their symmetry, perpendicular height changes and how these focal volume changes have produced a lift of the facial features below the areas you have treated.

Perpendicular height increases, shown as the ‘warmer’ colours are demonstrated in the volume treated areas. Perpendicular height decreases can be seen as ‘colder’ colours in the untreated mandibular and perioral regions. The interpretation is that the volume replacement has quantifiably improved physiological curves of the face AND produced an upward lift in contiguous regions. Other players have been on the right track talking about the O-G curve and shape of the face, but quantifying the degree of lift from perpendicular height changes where volume has been replaced is not only measurable at the site, where the high points exist, but quantifiable lift is demonstrated at the jowls, oral commissures and nasolabial folds using SAFV.

SAFV scanning cares less about ambient lighting conditions or accurate patient position, precise distance from object, depth of field, exposure times and can even measure the mildest expression difference as a factor in the evaluation of artefact.

The above information has been written by Dr Molton to provide further information on the SAFV system to doctors and other cosmetic medicine practitioners.

Medical and Technical Journal References

  1. Machine Learning Approaches for Prediction of Facial Rejuvenation Using Real and Synthetic Data:
    Bennamoun M, Molton M, Shah S February 2019 IEEE Access PP(99):1-1
  2. Improving the Face of Cosmetic Medicine: An Automatic Three-dimensional Analysis System for Facial Rejuvenation: Molton M, Bennamoun M
    July 2016Journal of Plastic Reconstructive & Aesthetic Surgery 2(2:12)
  3. A Training-Free Mesh Upsampling and Morphing Technique for 3D Face Rejuvenation: Bennamoun, M Molton M, Shah S : November 2018 10.1109/IVCNZ.2018.8634685 Conference: 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ)