DESIGNING AN EFFICIENT METHOD OF MULTI-STAGE COMPRESSION OF MAMMOGRAPHY IMAGES FOR OPTIMAL STORAGE AND TRANSMISSION BASED ON NEURAL NETWORK AND L-M ALGORITHM

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NOSRATINIA B.; HADDADNIA J.

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Journal: HOSPITAL Year:2015 | Volume:14 | Issue:2 (53) Page(s): 9-21

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Title

DESIGNING AN EFFICIENT METHOD OF MULTI-STAGE COMPRESSION OF MAMMOGRAPHY IMAGES FOR OPTIMAL STORAGE AND TRANSMISSION BASED ON NEURAL NETWORK AND L-M ALGORITHM

Author(s)

NOSRATINIA B. | HADDADNIA J. | Issue Writer Certificate

Keywords

CANCERQ2

BREAST PRINTSQ2

IMAGE PROCESSINGQ2

IMAGE COMPRESSION AND NEURAL NETWORKSQ2

Abstract

Introduction: In the process of telemedicine, the use of digital techniques for the diagnosis of diseases has made physicians to use ring resources and high bandwidth in data transfer for archiving and storing patient information.Methods: The aim of this paper is to introduce an efficient way of multi-stage compression of mammographic image data based LM algorithm and artificial neural networks. First, the data derived from mammographic images are given to multi-layer neural network and the proposed structure allows the sample images to be formed with the minimum damage and the degree of compaction in the first layer.Results: The compression process of the mammography images was implemented using images of 128 women aged 46.41±6.55 with a BMI of 36.78 ±5.5 collected from three specialized clinics in Sabzevar. The analysis yielded a mean square error (MSE) of 4.24 with the highest difference ratio of 33.46 and compression ratio of 8: 1in the output of the algorithm. The system performance was acceptable based on the accurate design of the software, and therefore it demonstrated high efficiency in practice.Conclusion: Given the reliability of software output in the compression and release and the fact that mammographic images are not completely degraded during compression, the diagnosis in the discovery stage is highly consistent with the diagnosis in the reality. Therefore, this system has the capacity to be implemented in hospitals for archiving mammography images and its application is justifiable.

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APA: Copy

NOSRATINIA, B., & HADDADNIA, J.. (2015). DESIGNING AN EFFICIENT METHOD OF MULTI-STAGE COMPRESSION OF MAMMOGRAPHY IMAGES FOR OPTIMAL STORAGE AND TRANSMISSION BASED ON NEURAL NETWORK AND L-M ALGORITHM. HOSPITAL, 14(2 (53)), 9-21. SID. https://sid.ir/paper/106682/en

Vancouver: Copy

NOSRATINIA B., HADDADNIA J.. DESIGNING AN EFFICIENT METHOD OF MULTI-STAGE COMPRESSION OF MAMMOGRAPHY IMAGES FOR OPTIMAL STORAGE AND TRANSMISSION BASED ON NEURAL NETWORK AND L-M ALGORITHM. HOSPITAL[Internet]. 2015;14(2 (53)):9-21. Available from: https://sid.ir/paper/106682/en

IEEE: Copy

B. NOSRATINIA, and J. HADDADNIA, “DESIGNING AN EFFICIENT METHOD OF MULTI-STAGE COMPRESSION OF MAMMOGRAPHY IMAGES FOR OPTIMAL STORAGE AND TRANSMISSION BASED ON NEURAL NETWORK AND L-M ALGORITHM,” HOSPITAL, vol. 14, no. 2 (53), pp. 9–21, 2015, [Online]. Available: https://sid.ir/paper/106682/en

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