Intelligent Image-Activated Cell Sorting

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligen...

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Bibliographic Details
Published in:	Cell 2018-09, Vol.175 (1), p.266-276.e13
Main Authors:	Nitta, Nao, Sugimura, Takeaki, Isozaki, Akihiro, Mikami, Hideharu, Hiraki, Kei, Sakuma, Shinya, Iino, Takanori, Arai, Fumihito, Endo, Taichiro, Fujiwaki, Yasuhiro, Fukuzawa, Hideya, Hase, Misa, Hayakawa, Takeshi, Hiramatsu, Kotaro, Hoshino, Yu, Inaba, Mary, Ito, Takuro, Karakawa, Hiroshi, Kasai, Yusuke, Koizumi, Kenichi, Lee, SangWook, Lei, Cheng, Li, Ming, Maeno, Takanori, Matsusaka, Satoshi, Murakami, Daichi, Nakagawa, Atsuhiro, Oguchi, Yusuke, Oikawa, Minoru, Ota, Tadataka, Shiba, Kiyotaka, Shintaku, Hirofumi, Shirasaki, Yoshitaka, Suga, Kanako, Suzuki, Yuta, Suzuki, Nobutake, Tanaka, Yo, Tezuka, Hiroshi, Toyokawa, Chihana, Yalikun, Yaxiaer, Yamada, Makoto, Yamagishi, Mai, Yamano, Takashi, Yasumoto, Atsushi, Yatomi, Yutaka, Yazawa, Masayuki, Di Carlo, Dino, Hosokawa, Yoichiroh, Uemura, Sotaro, Ozeki, Yasuyuki, Goda, Keisuke
Format:	Article
Language:	English
Subjects:	automation blood cells cellular heterogeneity cellular morphology convolutional neural network data collection decision making deep learning high-throughput microscopy high-throughput screening image-activated cell sorting information processing infrastructure machine intelligence medical sciences microalgae microscopy photosynthesis
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