Name
Title | ||
|---|---|---|
Simultaneous Cell Detection and Classification with an Asymmetric Deep Autoencoder in Bone Marrow Histology Images. |
Abstract | ||
|---|---|---|
Recently, deep learning approaches have been shown to be successful for analyzing histopathological images. In general, cell detection and classification are separated and assigned into two different networks, resulting in increased computational complexity for training the deep netwrok. Here we propose a novel deep autoencoder structure for classification with detection. This novel network uses one deep autoencoder to detect the positions of cells and classify types of cells simultaneously. In addition, the proposed network can efficiently detect the cells with irregular shape. The performance of the proposed method is shown to be similar to that of conventional deep learning approaches for detection and close to that of conventional deep learning approaches for classification. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-60964-5_72 | MIUA |
Field | DocType | Citations |
Autoencoder,Pattern recognition,Computer science,Digital pathology,Artificial intelligence,Deep learning,Radiology,Bone marrow,Bone marrow cancer | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| tzuhsi song | 1 | 4 | 1.42 |
| Victor Sanchez | 2 | 144 | 31.22 |
| hesham eidaly | 3 | 4 | 1.42 |
| Nasir Rajpoot | 4 | 544 | 46.45 |