Learning to Segment Breast Biopsy Whole Slide Images

8 Sep 2017Sachin MehtaEzgi MercanJamen BartlettDonald WeaverJoann ElmoreLinda Shapiro

We trained and applied an encoder-decoder model to semantically segment breast biopsy images into biologically meaningful tissue labels. Since conventional encoder-decoder networks cannot be applied directly on large biopsy images and the different sized structures in biopsies present novel challenges, we propose four modifications: (1) an input-aware encoding block to compensate for information loss, (2) a new dense connection pattern between encoder and decoder, (3) dense and sparse decoders to combine multi-level features, (4) a multi-resolution network that fuses the results of encoder-decoders run on different resolutions... (read more)

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