Optimization of block size for DCT-based medical image compression.

Area of Science:

• Medical imaging
• Image compression
• Digital signal processing

Background:

• Medical imaging generates vast amounts of data, necessitating efficient compression methods.
• Discrete Cosine Transform (DCT) is a widely used compression technique, but full-frame processing is computationally intensive.
• Block-based processing is employed to manage the computational load of DCT.

Purpose of the Study:

• To determine the optimal block size for Discrete Cosine Transform (DCT) based medical image compression.
• To balance processing time, compression ratio, and reconstructed image quality for CT, ultrasound, and X-ray images.

Main Methods:

• Investigated various block sizes for DCT compression of medical images.
• Evaluated performance based on processing time, compression ratio, and reconstruction quality.
• Utilized Benefit-to-Cost Ratio (BCR) and Reconstruction Quality Score (RQS) for quantitative comparison.

Main Results:

• Experimental results indicate that a 16x16 block size offers the best trade-off between compression efficiency and image quality.
• The 16x16 block size demonstrated optimal performance across CT, ultrasound, and X-ray image compression.

Conclusions:

• The 16x16 block size is optimal for Discrete Cosine Transform (DCT) based compression of medical images.
• This finding contributes to more efficient storage and transmission of critical diagnostic information in healthcare.