A deep learning-based approach for automated landmark extraction from 3dMD facial photographs was developed and its precision was evaluated. The results showed high precision and consistency in landmark annotation, comparable to manual and semi-automatic annotation methods.
Preoperative baseline breast measurements, age, and BMI can impact bra designs for breast cancer survivors who undergo autologous reconstruction due to size, shape, and symmetry changes. Bra needs of people who undergo autologous reconstruction differ from those who undergo implant-based reconstruction.
3dMD facial images and deep transfer learning have been firstly combined for evaluating the facial attractiveness in patients undergoing Orthognathic surgery.
The findings suggest that until age 6, there are no significant differences… therefore, efforts should be made to ensure early diagnosis so that minimally invasive surgery is a viable treatment option.
We present a fully automated pipeline to identify craniofacial landmarks in real time, and we use it to assess the head shape of patients with craniosynostosis using 3D photogrammetry.
Infants received 3dMD scans at 2 months of age, at clinical resolution of their head shape, and at 12 months of age. If their head shape was not resolved by 12 months of age, they received only two 3dMD scans (at 2 and 12 months of age).
We recently used surface imaging modalities to develop regional measures quantifying elongation in the frontal bossing index and occipital bullet index.
Use of 3D imaging for volume measurement in head and neck lymphedema has not been previously studied. Our study demonstrates that… it is an effective tool in evaluating head and neck lymphedema.
Quantitative measures of severity transcend cleft type and can be used to grade clinical severity.
Although patients may experience severe structural deformity and range of motion limitations, these factors do not appear to be associated with decreased physical activity level.