3dMD Announces the Next Generation of Downstream Dynamic-4D Image Analysis Software.
3dMD’s natural software evolution to more sophisticated dynamic-4D image analysis, landmark detection, and feature tracking capabilities.
Training AI, Wearing Tech,
and Imaging Health.
3dMD’s natural software evolution to more sophisticated dynamic-4D image analysis, landmark detection, and feature tracking capabilities.
In summary, this study will serve as evidence to guide clinicians in deciding whether to perform the T&A on patients prior to functional therapy based on a wide range of objectively and subjectively measured outcomes and provide a reference for multidisciplinary management of OSA with craniofacial alterations in growing children.
For infants up to age three months, 3D images were performed in our neonatal intermediate care unit in the supine position using a 10Hz 3dMDface.t System with this set-up being developed specifically for this study. Subsequently, 3D images were taken in an upright position with infants sitting on their parent’s lap in the department of orthodontics using a 10Hz 3dMDtrio.t system.
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.