@inproceedings{818dc30bd8224298b819b7c918180fff,
title = "Cell lineage tracing in lens-free microscopy videos",
abstract = "In vitro experiments with cell cultures are essential for studying growth and migration behaviour and thus, for gaining a better understanding of cancer progression and its treatment. While recent progress in lens-free microscopy (LFM) has rendered it an inexpensive tool for continuous monitoring of these experiments, there is only little work on analysing such time-lapse sequences. We propose (1) a cell detector for LFM images based on residual learning, and (2) a probabilistic model based on moral lineage tracing that explicitly handles multiple detections and temporal successor hypotheses by clustering and tracking simultaneously. (3) We benchmark our method on several hours of LFM time-lapse sequences in terms of detection and tracking scores. Finally, (4) we demonstrate its effectiveness for quantifying cell population dynamics.",
author = "Markus Rempfler and Sanjeev Kumar and Valentin Stierle and Philipp Paulitschke and Bjoern Andres and Menze, {Bjoern H.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 ; Conference date: 11-09-2017 Through 13-09-2017",
year = "2017",
doi = "10.1007/978-3-319-66185-8_1",
language = "English",
isbn = "9783319661841",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "3--11",
editor = "Pierre Jannin and Simon Duchesne and Maxime Descoteaux and Alfred Franz and Collins, {D. Louis} and Lena Maier-Hein",
booktitle = "Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings",
}
