@inproceedings{2f4b19696b42492c9b39b56cf99be1e9,
title = "Classifying protein crystallization trial images using subordinate color channel",
abstract = "This paper presents a new method of segmenting and classifying protein crystallization trial images that were collected using trace fluorescent labeling. Trace fluorescent labeling typically involves fluorescence dye that can re-emit the illumination light at other wavelengths around the principal wavelength. The captured image has a primary color channel with respect to illumination light and fluorescence dye. Crystals will have higher intensity than non-crystal areas. But there might be bright regions that may not be crystals, thereby making inaccurate and not robust trial images classification. In this paper, we utilize the subordinate color channel besides the primary color in the image of trace fluorescently labeled protein solution. This new method extracts proper features and successfully builds a high accuracy classifier with a low rate of misclassification of crystals as non-crystals. We also present a framework that could optimize both image segmentation and classification. In our experiments, we achieved around 94% accuracy with 0.6% misclassification of crystals as non-crystal.",
author = "Tran, {Truong X.} and Aygun, {Ramazan S.} and Pusey, {Marc L.}",
note = "Funding Information: Image segmentation is a critical application in many biomedical applications such as detecting cancer cells. This work shows how to improve the robustness of segmentation algorithms especially based on the light source. While accuracy is a simple human interpretable measure to evaluate the performance of a system, it may be misleading when sensitivity is more critical and the most significant class is comparatively less represented due to success rate. ACKNOWLEDGMENT This research was supported by National Institutes of Health (GM090453) grant and (GM116283) grant. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",
year = "2017",
month = dec,
day = "15",
doi = "10.1109/BIBM.2017.8217890",
language = "English (US)",
series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1546--1553",
editor = "Illhoi Yoo and Zheng, {Jane Huiru} and Yang Gong and Hu, {Xiaohua Tony} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",
booktitle = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",
address = "United States",
}