Adaptive Prediction Methods for Medical Image/Video compression for Telemedicine Application

Abstract

Due to rapid development of multimedia communication and advancement of image acquisition process, there is a crucial requirement of high storage and compression techniques to mitigate high data rate with limited bandwidth scenario for telemedicine application. Lossless compression is one of the challenging tasks in applications like medical, space, and aerial imaging field. Apart from achieving high compression ratio, in these mentioned applications there is a need to maintain the original imaging quality along with fast and adequate processing. Predictive coding was introduced to remove spatial redundancy. The accuracy of predictive coding is based on the choice of effective and adaptive predictor which is responsible for removing spatial redundancy. Medical images like computed tomography (CT) and magnetic resonance imaging (MRI) consume huge storage and utilize maximum available bandwidth. To overcome these inherent challenges, the authors have reviewed various adaptive predictors and it has been compared with existing JPEG and JPEG LS-based linear prediction technique for medical images.

Efficient Medical Video Streaming by Pre-Processing and Network Traffic Prioritization in Real-Time

“…The ROI is the key area in a frame that contains the required medical data for an accurate diagnosis and treatment. Hence, maintaining the quality and preserving data in ROI is necessary [12]. Further, de-noising also aids in the accurate segmentation of each frame in the video.…”

Masking of temporal activity for video quality control, measurement and assessment

“…Both these algorithms are able to remove unnecessary information to reduce the size of an image or video content. 2 Each person can have a different perception of the distortion depending on the information masked during the process. Motion or temporal masking (TM) can help adjust the relevance-distortion before quantifying its total amount.…”