DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation
Joint Authors
Teng, Lin
Li, Hang
Karim, Shahid
Source
Journal of Healthcare Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-12-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Medical image segmentation is one of the hot issues in the related area of image processing.
Precise segmentation for medical images is a vital guarantee for follow-up treatment.
At present, however, low gray contrast and blurred tissue boundaries are common in medical images, and the segmentation accuracy of medical images cannot be effectively improved.
Especially, deep learning methods need more training samples, which lead to time-consuming process.
Therefore, we propose a novelty model for medical image segmentation based on deep multiscale convolutional neural network (CNN) in this article.
First, we extract the region of interest from the raw medical images.
Then, data augmentation is operated to acquire more training datasets.
Our proposed method contains three models: encoder, U-net, and decoder.
Encoder is mainly responsible for feature extraction of 2D image slice.
The U-net cascades the features of each block of the encoder with those obtained by deconvolution in the decoder under different scales.
The decoding is mainly responsible for the upsampling of the feature graph after feature extraction of each group.
Simulation results show that the new method can boost the segmentation accuracy.
And, it has strong robustness compared with other segmentation methods.
American Psychological Association (APA)
Teng, Lin& Li, Hang& Karim, Shahid. 2019. DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation. Journal of Healthcare Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1175405
Modern Language Association (MLA)
Teng, Lin…[et al.]. DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation. Journal of Healthcare Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1175405
American Medical Association (AMA)
Teng, Lin& Li, Hang& Karim, Shahid. DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation. Journal of Healthcare Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1175405
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175405