Stacked Autoencoder for Segmentation of Bone Marrow Histological Images

被引：0

作者：

Oszutowska-Mazurek, Dorota ^{[1
]}

Mazurek, Przemyslaw ^{[2
]}

Knap, Oktawian ^{[3
]}

机构：

[1] Pomeranian Med Univ, Dept Epidemiol & Management, Zolnierska 48 St, PL-71210 Szczecin, Poland

[2] West Pomeranian Univ Technol, Dept Signal Proc & Multimedia Engn, 26 Kwietnia 10 St, PL-71126 Szczecin, Poland

[3] Pomeranian Med Univ, Dept Forens Med, Powstancow Wielkopolskich 72 St, PL-70111 Szczecin, Poland

来源：

ARTIFICIAL INTELLIGENCE AND ALGORITHMS IN INTELLIGENT SYSTEMS | 2019年 / 764卷

关键词：

Deep learning; Autoencoders; Stacked autoencoders; Image segmentation; Bone marrow;

D O I：

10.1007/978-3-319-91189-2_42

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Stacked autoencoder was used for the segmentation of trabeculas from bone marrow histological images derived from patients after hip joints arthroplasty. Additional filtering of areas smaller than 20000 pixels is necessary. The method has 95% efficiency. Proposed stacked autoencoder processes input images without special intervention automatically that is the main advantage of unsupervised learning over the supervised learning.

引用

页码：425 / 435

页数：11

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