Performance analysis and comparison of medical image compression techniques

Dinu, Anca; Kebede, Abraham Alem; Veerasamy, Balaji

doi:10.1109/iccicct.2016.7988050

Cited by 10 publications

(6 citation statements)

References 13 publications

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“…Pre-processing guarantees effective operation of disease analysis. The main purpose of data pre-processing is to reduce the amount of features used for classification method [8]. Data pre-processing techniques involves data collections and processing the information.…”

Section: Proposed Methods -Predictive K-nearest Neighbor Instance Based Approachmentioning

confidence: 99%

Early detection of Alzheimer's disease using predictive k-NN instance based approach and T-Test Method

Dinu¹

2019

IJATCSE

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Nowadays various neural network algorithms are used in the classification of clinical data for human conditions such as Alzheimer's disease, which can extract low-to-high-level features. Classification of clinical data for Alzheimer's disease has always been challenging as currently there is no clinical test for Alzheimer's disease. Doctors diagnose it by conducting assessments of patients' cognitive decline. But it's particularly difficult for them to identify mild cognitive impairment at an early stage when symptoms are less obvious. Also, it is difficult to predict whether patients will develop Alzheimer's disease or not. The accurate diagnosis of Alzheimer's disease in the early stage is important in order to take preventive measures and to reduce the severity and progression before irreversible brain damages occur. The effectiveness of abnormality detection depends on the accuracy and robustness of the algorithm used. Different machine learning techniques with different levels of sensitivity, efficiency, and accuracy have been developed. In this paper, a feature selection using T-Test method for joint regression and classification via instance based k-Nearest Neighbor classifier is proposed for Alzheimer's disease detection. Also, we compare the accuracy measures and performance of the proposed method with existing techniques in Alzheimer's disease detection. The new method gives a better accuracy results compared to conventional methods.

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Section: Proposed Methods -Predictive K-nearest Neighbor Instance Based Approachmentioning

confidence: 99%

Early detection of Alzheimer's disease using predictive k-NN instance based approach and T-Test Method

Dinu¹

2019

IJATCSE

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“…The outstanding compression technique will show low of MSE and high of PSNR. Most researchers prefer to use PSNR as the primary evaluation techniques and support by the compression ratio and MSE [17]. Figure 4 and Figure 5 shows the trend result of the compression image using CR and PSNR for the particular ROI-based hybrid medical image compression by previous studies.…”

Section: Telkomnika Telecommun Comput El Controlmentioning

confidence: 99%

“…Another part of the image's content is known as the background and the image's most ignored part. In the medical field, Many different parameters can be used to describe and compare the performance of a compression technique such as mean square error (MSE), peak signal to noise ratio (PSNR), compression ratio (CR), and time consumption to compress the image [11,17,18]. The compression ratio indicates the efficiency of the compression algorithm.…”

Section: Medical Image Compressionmentioning

confidence: 99%

A review on region of interest-based hybrid medical image compression algorithms

Aziz

Sam

Mohamed³

et al. 2020

TELKOMNIKA

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Digital medical images have become a vital resource that supports decision-making and treatment procedures in healthcare facilities. The medical image consumes large sizes of memory, and the size keeps on growth due to the trend of medical image technology. The technology of telemedicine encourages the medical practitioner to share the medical image to support knowledge sharing to diagnose and analyse the image. The healthcare system needs to ensure distributes the medical image accurately with zero loss of information, fast and secure. Image compression is beneficial in ensuring that achieve the goal of sharing this data. The region of interest-based hybrid medical compression algorithm plays the parts to reduce the image size and shorten the time of medical image compression process. Various studies have enhanced by combining numerous techniques to get an ideal result. This paper reviews the previous works conducted on a region of interest-based hybrid medical image compression algorithms.

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“…Data and communication exchange between medical devices is characterized by a set of standards that are detailed in what follows. DICOM (Digital Imaging and Communications in Medicine) is a standard developed by the National Electrical Manufacturers Association (NEMA) to store retrieve and transfer medical imaging from various medical devices such as scanners, printers, network hardware etc [23]. DICOM promotes digital information exchange between medical imaging equipment and other systems, and therefore medical imaging is done between physicians or medical centers in an interoperable way.…”

Section: Medical Devices and Medical Communication Standardsmentioning

confidence: 99%

Medical systems, the role of middleware and survey on middleware design

Touahria

2018

Preprint

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The integration of medical devices in the patient treatment process becomes increasingly important due to the efficiency of the technology. On the one hand, medical devices hardware is more powerful and its integration with the software platforms is improved. These devices are able to transfer accurate data to the clinician and offer the possibility of sharing data with other devices or computational servers for advanced analysis. On the other hand, medical software platforms are appearing to provide advanced functionality on top of these medical hardware devices. In this context, the role of the software is essential, not only at the highest abstraction level that provides the application business logic; the role of the underlying connecting software (the communication middleware or distribution software) is essential. These are capable of providing advanced connectivity functions, very efficiently, and within appropriate time bounds. This paper reviews the state of the art on middleware as facilitator for interconnection among devices and also describes a number of initiatives (such as the Integrated Clinical Environment -ICE) and projects that further extend the underlying distribution software towards the clinical domain as device interconnection facilitators.

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Performance analysis and comparison of medical image compression techniques

Cited by 10 publications

References 13 publications

Early detection of Alzheimer's disease using predictive k-NN instance based approach and T-Test Method

Early detection of Alzheimer's disease using predictive k-NN instance based approach and T-Test Method

A review on region of interest-based hybrid medical image compression algorithms

Medical systems, the role of middleware and survey on middleware design

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