TY - JOUR
T1 - Learning-based cell detection in digital pathology
AU - Ren, Zhenbo
AU - Lam, Edmund Y.
AU - Zhao, Jianlin
N1 - Publisher Copyright:
© OSA 2021, © 2021 The Author(s)
PY - 2021
Y1 - 2021
N2 - In blood testing, knowing the ratio and throughput of blood cells is crucial to help doctors make a clinical diagnosis. Here we propose a deep transfer learning strategy for accurate cell detection for digital pathology.
AB - In blood testing, knowing the ratio and throughput of blood cells is crucial to help doctors make a clinical diagnosis. Here we propose a deep transfer learning strategy for accurate cell detection for digital pathology.
UR - http://www.scopus.com/inward/record.url?scp=85119403145&partnerID=8YFLogxK
M3 - 会议文章
AN - SCOPUS:85119403145
SN - 2162-2701
JO - Optics InfoBase Conference Papers
JF - Optics InfoBase Conference Papers
M1 - JW1A.184
T2 - CLEO: QELS_Fundamental Science, CLEO: QELS 2021 - Part of Conference on Lasers and Electro-Optics, CLEO 2021
Y2 - 9 May 2021 through 14 May 2021
ER -