Related Experiment Videos
Advances in high-speed, three-dimensional imaging and automated segmentation algorithms for thick and overlapped
R W Mackin1, L M Newton, J N Turner
1Electrical, Computer and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, New York, USA.
Objective:
To use three-dimensional (3-D) imaging and localized adaptive image analysis to enable automated cervical smear screening systems to efficiently and effectively process thick and overlapped cell clusters currently left unprocessed.
Study Design:
Instrumentation was developed to perform high-speed (50-200 optical sections per second at 256 x 256 resolution), 3-D imaging of thick regions of cervical smears. Normal and abnormal ThinPrep smears were imaged at two levels of resolution to approximate higher-resolution, wide-area imaging. Improved dual-resolution, 3-D image analysis algorithms were developed for segmenting nuclei in these clusters.
Results:
Despite low contrast, high variability and dense overlaps, the algorithms detected 89% and correctly segmented 76% of nuclei in clusters from normal smears and detected 75% and correctly segmented 45% of nuclei in clusters from abnormal smears in low-resolution images. In high-resolution images they detected 88% and segmented 76% of nuclei from normal specimens and detected 55% and segmented 45% of nuclei from abnormal specimens. At least one nucleus from each cell cluster was correctly segmented.
Conclusion:
Selective application of 3-D imaging and 3-D image analysis to thick and overlapped regions can enable a significant fraction (45-89%) of clustered and embedded cells to be accessed by an automated analysis system. These regions are, for the most part, unprocessable by current two-dimensional methods.