Customized design of hearing aids using statistical shape learning.
3D shape modeling is a crucial component of rapid prototyping systems that customize shapes of implants and prosthetic devices to a patient's anatomy. In this paper, we present a solution to the problem of customized 3D shape modeling using a statistical shape analysis framework. We design a novel method to learn the relationship between two classes of shapes, which are related by certain operations or transformation. The two associated shape classes are represented in a lower dimensional manifold, and the reduced set of parameters obtained in this subspace is utilized in an estimation, which is exemplified by a multivariate regression in this paper. We demonstrate our method with a felicitous application to estimation of customized hearing aid devices.
Unal
Gozde
G
Faculty of Engineering and Natural Sciences, Sabanci University, Turkey. gozdeunal@sabanciuniv.edu
Nain
Delphine
D
Slabaugh
Greg
G
Fang
Tong
T
D000465:Algorithms; D017076:Computer-Aided Design; D006310:Hearing Aids; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011474:Prosthesis Design / Q000379:methods*; D017755:Prosthesis Fitting / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity