@inproceedings{e802e2de98364b75ac2d63e95e77b568,
title = "Multiresolution image analysis for automatic quantification of collagen gel contraction",
abstract = "Quantifying collagen gel contraction is important in tissue engineering and biological research because it provides spatial-temporal assessments of cell behaviors and tissue material properties. However, these assessments currently rely on manual processing, which is time-consuming and subjective to personal opinions. We present a multiresolution image analysis system for automatic quantification of gel contraction. This system includes a color conversion process to normalize and enhance the contrast between gel and background. Then, a deformable circular model is activated automatically to capture details of gel boundaries. These steps are coordinated by a multiresolution strategy. The target measurements are obtained after gel segmentation. Our experiments using 30 images demonstrated a high consistency between the proposed and manual segmentation methods. The system can process large-size images (4000x3000) at a rate of approximately one second per image. It thus serves as a useful tool for analyzing large biological and biomaterial imaging datasets efficiently and objectively.",
keywords = "deformable model, gel contraction, multiresolution",
author = "Chen, {Hsin Chen} and Yang, {Tai Hua} and Thoreson, {Andrew R.} and Chunfeng Zhao and Amadio, {Peter C.} and Su, {Fong Chin} and Wenyan Jia and Sun, {Yung Nien} and An, {Kai Nan} and Mingui Sun",
year = "2013",
doi = "10.1109/NEBEC.2013.115",
language = "English (US)",
isbn = "9780769549644",
series = "Proceedings of the IEEE Annual Northeast Bioengineering Conference, NEBEC",
pages = "64--65",
booktitle = "Proceedings - 39th Annual Northeast Bioengineering Conference, NEBEC 2013",
note = "39th Annual Northeast Bioengineering Conference, NEBEC 2013 ; Conference date: 05-04-2013 Through 07-04-2013",
}