Stacked Autoencoder for Segmentation of Bone Marrow Histological Images

摘要

Stacked autoencoder was used for the segmentation of tra-beculas 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.