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Edge-shrinking Interpolation for Medical Images by Yuh-Hwan Liu; Yung-Nien Sun; Chi-Wu Mao; Chii-Jeng Lin is a Medicine article available to read on EtoBox.

What is Edge-shrinking Interpolation for Medical Images about?

Abstrac&--A new algori&m for interpolating the missing data between two adjacent mediial images is presented. Our method is useful for solving the interpolation of any region-represented images of an object to be reconstructed, even when the object is stretched abruptly, branched or hollow, as often occurs in medical images, which cases can not be handled well by existing methods. When this algorithm is applied, the nonoverlapped region of the same object in the two hase images are first extracted and encodd by chamfer distance code on every pixel in these regions. Then, the outer edge of the nonoverlappk region are shrunk inward simultaneously so that the stretched edges reach the edges of the overlapping regions at t4u? same time. The distance codes in nonoverlapping regions are used to limit the shriiing of these edges in the interpolation process. The proposed method also provides object centralization and enlargement opera&~ to obtain stable and reasonable results in complicated case. The experimental results show that the pNposed method is more effective and efficient in resolving general interpolation tasks than the existing methods (S.

Who reads Edge-shrinking Interpolation for Medical Images?

Author

Yuh-Hwan Liu; Yung-Nien Sun; Chi-Wu Mao; Chii-Jeng Lin

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0895-6111)

Published

1997

Language

EN

Field

Medicine (Health Sciences)