Modified Discrete Wavelet Transformation to Compress DICOM Medical Images with Run-Length Encoding

With rapid advancements in medical imaging tech-nology, a substantial amount of image data has been produced to assist clinical diagnostics. Nevertheless, storing and trans-mitting medical images with high-resolution content presents a formidable challenge that needs to be addressed. This study pro-poses a technique to compress DICOM images using a Modified variant of Discrete Wavelet Transform (MDWT) including Run-Length Encoding and DEFLATE algorithm. The proposed mech-anism decomposes a DICOM image into its frequency sub-bands, namely, approximation (LL), horizontal detail (LH), vertical detail (HL), and diagonal detail (HH) coefficients which are then thresholded and quantized in an adaptive manner using uniform scalar quantization. The quantized coefficients are run-length encoded with a modified scheme to traverse the data including linear, diagonal, and spiral approaches. Subsequently, DEFLATE algorithm-based compression is performed for further reduction in data volume. Results indicate a noteworthy improvement in compression ratio with the modifications while preserving a high level of detail.