Conference proceeding
Cell Segmentation, Tracking, and Mitosis Detection Using Temporal Context
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005, pp.302-309
Lecture Notes in Computer Science
2005
DOI: 10.1007/11566465_38
Abstract
The Large Scale Digital Cell Analysis System (LSDCAS) developed at the University of Iowa provides capabilities for extended-time live cell image acquisition. This paper presents a new approach to quantitative analysis of live cell image data. By using time as an extra dimension, level set methods are employed to determine cell trajectories from 2D + time data sets. When identifying the cell trajectories, cell cluster separation and mitotic cell detection steps are performed. Each of the trajectories corresponds to the motion pattern of an individual cell in the data set. At each time frame, number of cells, cell locations, cell borders, cell areas, and cell states are determined and recorded. The proposed method can help solving cell analysis problems of general importance including cell pedigree analysis and cell tracking. The developed method was tested on cancer cell image sequences and its performance compared with manually-defined ground truth. The similarity Kappa Index is 0.84 for segmentation area and the signed border positioning segmentation error is 1.6 ± 2.1 μm.
Details
- Title: Subtitle
- Cell Segmentation, Tracking, and Mitosis Detection Using Temporal Context
- Creators
- Fuxing Yang - Department of Electrical and Computer Engineering,Michael A Mackey - Departments of Pathology and Biomedical Engineering,Fiorenza Ianzini - Department of Radiation Oncology, The University of Iowa, Iowa CityGreg Gallardo - Department of Electrical and Computer Engineering,Milan Sonka - Department of Electrical and Computer Engineering,
- Resource Type
- Conference proceeding
- Publication Details
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005, pp.302-309
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/11566465_38
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Language
- English
- Date published
- 2005
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984047727302771
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