Conference proceeding
Automatic summarization of changes in image sequences using algorithmic information theory
2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, pp 859-862
01 Jan 2008
Abstract
An algorithmic information theoretic method is presented for object-level summarization of meaningful changes in image sequences. Object extraction and tracking data are represented as an attributed tracking graph (ATG), whose connected subgraphs are compared using an adaptive information distance measure, aided by a closed-form multi-dimensional quantization. The summary is the clustering result and feature subset that maximize the gap statistic. The notion of meaningful summarization is captured by using the gap statistic to estimate the randomness deficiency from algorithmic statistics. When applied to movies of cultured neural progenitor cells, it correctly distinguished neurons from progenitors without requiring the use of a fixative stain. When analyzing intra-cellular molecular transport in cultured neurons undergoing axon specification, it automatically confirmed the role of kinesins in axon specification. Finally, it was able to differentiate wild type from genetically modified thymocyte cells.
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Details
- Title
- Automatic summarization of changes in image sequences using algorithmic information theory
- Creators
- Andrew R. Cohen - Rensselaer Polytechnic InstituteChristopher Bjornsson - Rensselaer Polytechnic InstituteYing Chen - Rensselaer Polytechnic InstituteGary Banker - Oregon Health & Science UniversityEna Ladi - University of California, BerkeleyEllen Robey - University of California, BerkeleySally Temple - Albany Medical Center HospitalBadrinath Roysam - Rensselaer Polytechnic InstituteIEEE
- Publication Details
- 2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, pp 859-862
- Series
- IEEE International Symposium on Biomedical Imaging
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- EEC-9986821 / Center for Subsurface Sensing and Imaging Systems under the Engineering Research Centers Program of the US National Science Foundation Rensselaer Polytechnic Institute
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000258259800216
- Scopus ID
- 2-s2.0-51049088823
- Other Identifier
- 991019296868304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Biomedical
- Engineering, Electrical & Electronic
- Imaging Science & Photographic Technology
- Nanoscience & Nanotechnology