TY - JOUR
T1 - Quantifying subtle locomotion phenotypes of Drosophila larvae using internal structures based on FIM images
AU - Risse, Benjamin
AU - Berh, Dimitri
AU - Otto, Nils
AU - Jiang, Xiaoyi
AU - Klämbt, Christian
PY - 2015/8/1
Y1 - 2015/8/1
N2 - Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.
AB - Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.
U2 - 10.1016/j.compbiomed.2014.08.026
DO - 10.1016/j.compbiomed.2014.08.026
M3 - Article
SN - 0010-4825
VL - 63
SP - 269
EP - 276
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
ER -