Head CT Image Convolution Feature Segmentation and Morphological Filtering for Densely Matching Points of IoTs
With the rapid application of medical imaging technology, the number of medical images is increasing and the form is gradually diversified. The management and retrieval of medical images is an urgent problem to solve. Traditional image matching technology has many limitations due to the complexity o...
Main Authors: | Yao Yao, Changlin Xia, Jitao Li, Qiong Li |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8949508/ |
Similar Items
-
A Novel Multi-Feature Representation of Images for Heterogeneous IoTs
by: Laihang Yu, et al.
Published: (2016-01-01) -
Cross-Media Semantic Matching based on Sparse Representation
by: Gongwen Xu*, et al.
Published: (2019-01-01) -
Assessing challenges and rate of matching Content Retrieval Conformity with Images in Scientific Databases
by: Adel Soleimani Nezhad, et al.
Published: (2019-12-01) -
Building Topic-Driven Virtual IoTs in a Multiple IoTs Scenario
by: Paolo Lo Giudice, et al.
Published: (2019-07-01) -
Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP
by: Xin Liu
Published: (2020-01-01)