TY - GEN
T1 - Mobile scanner for protein crystallization plates
AU - Shrestha, Ashok
AU - Tran, Truong
AU - Aygun, Ramazan
AU - Pusey, Marc L.
N1 - Funding Information:
ACKNOWLEDGMENT This research was supported by National Institutes of Health (GM116283) grant.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Protein crystallization well plate is a rectangular platform that contains wells usually organized as a grid structure. The crystallization conditions are studied through a screening process by setting up the trial conditions in the well plate. In the past, the expert evaluates the trial wells for the growth of crystals by manually viewing the plate under a microscope or using a high-throughput plate imaging and analysis system. While the first method is tedious and cumbersome, the second method requires financial investment. Recently, a few approaches were developed by collecting images using smartphones thus enabling low-cost automatic scoring (classification) of well images. Nevertheless, these recent methods do not detect which well on the plate is captured. If the user has a smartphone, the user may capture or scan any well by just moving the smartphone to the corresponding well. In this paper, we propose a mobile scanner that identifies the well by using a coded template under the well plate. The mobile scanner provides two modes: image and video. Image mode is used for single well analysis whereas video mode is used to scan the complete plate. In the video mode, the mobile scanner app generates a tilemap of the plate.
AB - Protein crystallization well plate is a rectangular platform that contains wells usually organized as a grid structure. The crystallization conditions are studied through a screening process by setting up the trial conditions in the well plate. In the past, the expert evaluates the trial wells for the growth of crystals by manually viewing the plate under a microscope or using a high-throughput plate imaging and analysis system. While the first method is tedious and cumbersome, the second method requires financial investment. Recently, a few approaches were developed by collecting images using smartphones thus enabling low-cost automatic scoring (classification) of well images. Nevertheless, these recent methods do not detect which well on the plate is captured. If the user has a smartphone, the user may capture or scan any well by just moving the smartphone to the corresponding well. In this paper, we propose a mobile scanner that identifies the well by using a coded template under the well plate. The mobile scanner provides two modes: image and video. Image mode is used for single well analysis whereas video mode is used to scan the complete plate. In the video mode, the mobile scanner app generates a tilemap of the plate.
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U2 - 10.1109/ISM.2018.000-5
DO - 10.1109/ISM.2018.000-5
M3 - Conference contribution
AN - SCOPUS:85061651565
T3 - Proceedings - 2018 IEEE International Symposium on Multimedia, ISM 2018
SP - 209
EP - 214
BT - Proceedings - 2018 IEEE International Symposium on Multimedia, ISM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Symposium on Multimedia, ISM 2018
Y2 - 10 December 2018 through 12 December 2018
ER -