The Library
Simultaneous cell detection and classification in bone marrow histology images
Tools
Song, Tzu-Hsi, Sanchez Silva, Victor, ElDaly, Hesham and Rajpoot, Nasir M. (2019) Simultaneous cell detection and classification in bone marrow histology images. IEEE Journal of Biomedical and Health Informatics, 23 (4). 1469 -1476. doi:10.1109/JBHI.2018.2878945 ISSN 2168-2194.
|
PDF
WRAP-simultaneous-cell-detection-classification-bone-marrow-Rajpoot-2018.pdf - Accepted Version - Requires a PDF viewer. Download (6Mb) | Preview |
Official URL: http://dx.doi.org/10.1109/JBHI.2018.2878945
Abstract
Recently, deep learning frameworks have been shown to be successful and efficient in processing digital histology images for various detection and classification tasks. Among these tasks, cell detection and classification are key steps in many computer-assisted diagnosis systems. Traditionally, cell detection and classification is performed as a sequence of two consecutive steps by using two separate deep learning networks, one for detection and the other for classification. This strategy inevitably increases the computational complexity of the training stage. In this paper, we propose a synchronized deep autoencoder network for simultaneous detection and classification of cells in bone marrow histology images. The proposed network uses a single architecture to detect the positions of cells and classify the detected cells, in parallel. It uses a curve-support Gaussian model to compute probability maps that allow detecting irregularly-shape cells precisely. Moreover, the network includes a novel neighborhood selection mechanism to boost the classification accuracy. We show that the performance of the proposed network is superior than traditional deep learning detection methods and very competitive compared to traditional deep learning classification networks. Runtime comparison also shows that our network requires less time to be trained.
Item Type: | Journal Article | ||||||||
---|---|---|---|---|---|---|---|---|---|
Subjects: | R Medicine > RB Pathology | ||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||
Library of Congress Subject Headings (LCSH): | Histology, Pathological, Bone marrow -- Biopsy-- Classification | ||||||||
Journal or Publication Title: | IEEE Journal of Biomedical and Health Informatics | ||||||||
Publisher: | IEEE | ||||||||
ISSN: | 2168-2194 | ||||||||
Official Date: | July 2019 | ||||||||
Dates: |
|
||||||||
Volume: | 23 | ||||||||
Number: | 4 | ||||||||
Page Range: | 1469 -1476 | ||||||||
DOI: | 10.1109/JBHI.2018.2878945 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Reuse Statement (publisher, data, author rights): | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 2 November 2018 | ||||||||
Date of first compliant Open Access: | 2 November 2018 |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year