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An adaptive source-channel coding with feedback for progressive transmission of medical images.

Lo JL, Sanei S, Nazarpour K - Int J Telemed Appl (2009)

Bottom Line: Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends.The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel.The experimental results verify the effectiveness of the design.

View Article: PubMed Central - PubMed

Affiliation: Centre of Digital Signal Processing, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK.

ABSTRACT
A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design.

No MeSH data available.


Related in: MedlinePlus

Lengths of the parity codes based on various channel noise levels.
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fig6: Lengths of the parity codes based on various channel noise levels.

Mentions: An adaptivevariable parity allocation requires the error between the transmitted image I(x, y) and the received image to be minimized under the desired conditions.Suppose that the error is defined as (7)ε=∥I(x,y)−I^(x,y)∥2, where //·//2 denotes the I2-norm.Generally, we wish to have the optimum parity length such that (8)Copt=minC ε  subject  to  ε≤εT, where εT is an acceptable error level in the receiver.According to the above discussion, the parity length can be defined as (9)C=g(r,SN)=f(r,BER), where S/N and BER stand, respectively, forsignal-to-noise ratio and bit-error rate (the BER here represents the noise situation in thechannel and does not refer to the output bit-error rate). The functions g and f are generally nonlinear functions, which can be definedempirically based on a number of trials. From Figure 5, f~(α0 − αr) for a fixed BER, where r ismeasured with respect to the number of pixels, and from Figure 6, it can beconcluded that f~(β BER + β0) for fixed proximity distance r. In more general applications, a more accurate and possibly complicated functionmay be adopted. Therefore, a reasonably accurate function can be modeled as (10)f(r,BER)=(α0−αr)(β BER+β0), or (11)f(r,BER)=μ3BER−μ2r⋅BER−μ1r+μ0, where μis are constant coefficients andcan be easily found based on Figures 5 and 6.


An adaptive source-channel coding with feedback for progressive transmission of medical images.

Lo JL, Sanei S, Nazarpour K - Int J Telemed Appl (2009)

Lengths of the parity codes based on various channel noise levels.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2630534&req=5

fig6: Lengths of the parity codes based on various channel noise levels.
Mentions: An adaptivevariable parity allocation requires the error between the transmitted image I(x, y) and the received image to be minimized under the desired conditions.Suppose that the error is defined as (7)ε=∥I(x,y)−I^(x,y)∥2, where //·//2 denotes the I2-norm.Generally, we wish to have the optimum parity length such that (8)Copt=minC ε  subject  to  ε≤εT, where εT is an acceptable error level in the receiver.According to the above discussion, the parity length can be defined as (9)C=g(r,SN)=f(r,BER), where S/N and BER stand, respectively, forsignal-to-noise ratio and bit-error rate (the BER here represents the noise situation in thechannel and does not refer to the output bit-error rate). The functions g and f are generally nonlinear functions, which can be definedempirically based on a number of trials. From Figure 5, f~(α0 − αr) for a fixed BER, where r ismeasured with respect to the number of pixels, and from Figure 6, it can beconcluded that f~(β BER + β0) for fixed proximity distance r. In more general applications, a more accurate and possibly complicated functionmay be adopted. Therefore, a reasonably accurate function can be modeled as (10)f(r,BER)=(α0−αr)(β BER+β0), or (11)f(r,BER)=μ3BER−μ2r⋅BER−μ1r+μ0, where μis are constant coefficients andcan be easily found based on Figures 5 and 6.

Bottom Line: Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends.The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel.The experimental results verify the effectiveness of the design.

View Article: PubMed Central - PubMed

Affiliation: Centre of Digital Signal Processing, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK.

ABSTRACT
A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design.

No MeSH data available.


Related in: MedlinePlus