Automatic Deformity Estimation for Thoracic Section Between Inhale and Exhale Positions

作者：Abidi Ali Imam^*; Singh Sanjay Kumar; Aggarwal Lalit M

来源：National Academy Science Letters-India, 2016, 39(5): 347-352.

DOI：10.1007/s40009-016-0451-3

• Control points
• Deformable images
• Automatic control point selection
• SURF
• Moving least squares
• Robust
• Average point translation

Corresponding control point pairs or landmarks in images can be used to define the deformation with respect to time, point of view or modality. Manual definition of the number of control points in an image, enough to define all kinds of deformation is a tedious task. Hence, automatic definition of control points is the way forward taken in this proposed work. The paper proposes an automatic registration process for tracing of the deformity path of the thoracic region based on feature detector speeded up robust feature (SURF) and moving least squares (MLS). The set of control points on the images is defined by its feature set which is obtained by using the SURF detector, which serves as input for MLS algorithm to trace the deformations of the image (thoracic image in this case). The credibility and performance of the above proposed method is demonstrated by its outstanding experimental results.

• 出版日期2016-10
• 单位河北医科大学