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Finding cancerous anaplastic cells with image analysis
Author(s) -
Nicol Kathleen,
Plaskow Mark Edward,
Barr Thomas,
Billiter Dave
Publication year - 2009
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.23.1_supplement.38.11
Subject(s) - computer science , digital image analysis , pathology , artificial intelligence , computer vision , medicine
Objective Advancing cancer research and location with image analysis Method The application was built using Microsoft technologies including Visual Basic 6.0, Visual Basic .NET, C++.NET, and SQLServer 2000‐2005. Key points of interest for anaplastic cells are stored in a database during the batching process, allowing for fast retrieval of areas for visual confirmation and analysis. Results 87% of all anaplastic nuclei analyzed were located, counted, and highlighted for the using pathologist/reviewer. Conclusion Lack of differentiation in cell nuclei is a constant marker for malignancy. With technology, programming, and image analysis breakthroughs such diffusion of nuclei is able to be located for pathologists across cases, studies, slide libraries, etc. using digital pathology. Our team's pixel analysis and experience makes possible the location of nuclei, cytoplasm, and connective tissue areas within digitized slides for measuring, highlighting, counting, etc. Pathologists are able to get electronic decision support in rapidly finding certain features for malignant cancerous tumors.