JPEG2000 ROI coding through component priority for digital mammography

Region Of Interest (ROI) coding is a prominent feature of some image coding systems aimed to prioritize specific areas of the image through the construction of a codestream that, decoded at increasing bit-rates, recovers the ROI first and with higher quality than the rest of the image. JPEG2000 is a wavelet-based coding system that is supported in the Digital Imaging and Communications in Medicine (DICOM) standard. Among other features, JPEG2000 provides lossy-to-lossless compression and ROI coding, which are especially relevant to the medical community. But, due to JPEG2000 supported ROI coding methods that guarantee lossless coding are not designed to achieve a high degree of accuracy to prioritize ROIs, they have not been incorporated in the medical community. - This paper introduces a ROI coding method that is able to prioritize multiple ROIs at different priorities, guaranteeing lossy-to-lossless coding. The proposed ROI Coding Through Component Prioritization (ROITCOP) method uses techniques of rate-distortion optimization combined with a simple yet effective strategy of ROI allocation that employs the multi-component support of JPEG2000 codestream. The main insight in ROITCOP is the allocation of each ROI to an component. Experimental results indicate that this ROI allocation strategy does not penalize coding performance whilst achieving an unprecedented degree of accuracy to delimit ROIs. - The proposed ROITCOP method maintains JPEG2000 compliance, thus easing its use in medical centers to share images. This paper analyzes in detail the use of ROITCOP to mammographies, where the ROIs are identified by computer-aided diagnosis. Extensive experimental tests using various ROI coding methods suggest that ROITCOP achieves enhanced coding performanc

An efficient error resilience scheme based on Wyner-Ziv coding for region-of-interest protection of wavelet based video transmission

In this paper, we propose a bandwidth efficient error resilience scheme for wavelet based video transmission over wireless channel by introducing an additional Wyner-Ziv (WZ) stream to protect region of interest (ROI) in a frame. In the proposed architecture, the main video stream is compressed by a generic wavelet domain coding structure and passed through the error prone channel without any protection. Meanwhile, the predefined ROI area related wavelet coefficients obtained after an integer wavelet transform will be specially protected by WZ codec in an additional channel during transmission. At the decoder side, the error-prone ROI related wavelet coefficients will be used as side information to help decoding the WZ stream. Different size of WZ bit streams can be applied in order to meet different bandwidth condition and different requirement of end users. The simulation results clearly revealed that the proposed scheme has distinct advantages in saving bandwidth comparing with fully applied FEC algorithm to whole video stream and in the meantime offer the robust transmission over error prone channel for certain video applications

Hybrid Region-based Image Compression Scheme for Mamograms and Ultrasound Images

The need for transmission and archive of mammograms and ultrasound Images has dramatically increased in tele-healthcare applications. Such images require large amount of' storage space which affect transmission speed. Therefore an effective compression scheme is essential. Compression of these images. in general. laces a great challenge to compromise between the higher compression ratio and the relevant diagnostic information. Out of the many studied compression schemes. lossless . IPl. (i- LS and lossy SPII IT are found to he the most efficient ones. JPEG-LS and SI'll IT are chosen based on a comprehensive experimental study carried on a large number of mammograms and ultrasound images of different sizes and texture. The lossless schemes are evaluated based on the compression ratio and compression speed. The distortion in the image quality which is introduced by lossy methods evaluated based on objective criteria using Mean Square Error (MSE) and Peak signal to Noise Ratio (PSNR). It is found that lossless compression can achieve a modest compression ratio 2: 1 - 4: 1. bossy compression schemes can achieve higher compression ratios than lossless ones but at the price of the image quality which may impede diagnostic conclusions. In this work, a new compression approach called Ilvbrid Region-based Image Compression Scheme (IIYRICS) has been proposed for the mammograms and ultrasound images to achieve higher compression ratios without compromising the diagnostic quality. In I LYRICS, a modification for JPI; G-LS is introduced to encode the arbitrary shaped disease affected regions. Then Shape adaptive SPIT IT is applied on the remaining non region of interest. The results clearly show that this hybrid strategy can yield high compression ratios with perfect reconstruction of diagnostic relevant regions, achieving high speed transmission and less storage requirement. For the sample images considered in our experiment, the compression ratio increases approximately ten times. However, this increase depends upon the size of the region of interest chosen. It is also föund that the pre-processing (contrast stretching) of region of interest improves compression ratios on mammograms but not on ultrasound images