JSAI2018

Presentation information

Poster presentation

General Session » Interactive

[4Pin1] インタラクティブ(2)

Fri. Jun 8, 2018 9:00 AM - 10:40 AM Room P (4F Emerald Lobby)

9:00 AM - 10:40 AM

[4Pin1-47] Bit-pattern kernel filtering for duplication removing in cell annotation.

〇Toru Nagasaka1 (1. AI & Eye Co., Ltd.)

Keywords:deep learning, image processing, kernel filtering, cell count, pathological diagnosis

In recent years, deep learning architectures have been shown to achieve good classification performance and a digital histopathology image analysis has been used in clinical settings. A partial image which are sequentially cropped from same cell by grid search may result in double counting. In this work, we constructed bit-pattern kernel filtering algorithm to remove duplication in cell annotation. Using unique combination of bit-pattern kernel (3x3) filter which contract particular ON-pixel pattern, the duplication remove in cell annotation was achieved.