DICOM MEDICAL IMAGE RETRIEVAL USING DEEP LEARNING ARCHITECTURE
Author’s Name : K. MENAKA, Dr. M. VANITHA
Volume 06 Issue 01 Year 2019 ISSN No: 2349-3828 Page no: 13-17
Abstract:
In this paper, a system is presented that locates reference tag sand image processing for DCM image retrieval. This technique performs the tag matching directly in the images bypassing parameter recognition and using classes as queries. First, it makes use of DCM image processing techniques, in order to extract powerful features for the description of the tag of the images. The features used for the comparison are capable of capturing the general shape of the query and its classes based on tags of the image. In order to demonstrate the effectiveness of our system, we used a collection of 22 classes in the data base and we trained all classes by tags and image classification by deep learning algorithm used to gain the rate of retrieval in the MATLAB GUI.
Keywords:
DICOM, Image retrival, MATLAB GUI
References:
- Zhe Wang, Yuan Liang, David C. Zhu and Tongtong Li,“The Relationship of Discrete DCM and Directed Information in fMRI based Causality Analysis”, IEEE Transactions on Molecular, Biological and Multi-Scale Communications – 2018 .
- Ching-Ting Tu, Yu-Hsien Chan, and Yi-Chung Chen, “Facial Sketch Synthesis Using Two-dimensional Direct Combined Model-based Face-Specific Markov Network”, IEEE Communications Letters – 2018.
- Jee-Hye Lee, Myung-Sun Baek, and Hyoung-Kyu Song “Improved Performance of Soft Decision Decoding for DCM in MB-OFDM SystemCongress on Image and Signal Processing – 2008.
- Boqiang Liu, Minghui Zhu, Zhenwang Zhang, Cong Yin, Zhongguo Liu, Jason Gu “Medical Image Conversion with DICOM”, Canadian Conference on Electrical and Computer Engineering – 2007.
- M. Brindha “Confidentiality, Integrity and authentication of DICOM medical images”, International Conference on Inventive Systems and Control (2018).