A new framework for effective communication and evaluation of wireless medical video over error-prone channels is proposed. This is motivated by the need to efficiently address unique requirements associated with medical video source encoding, wireless transmission, and quality assessment. The envisioned utilization scenarios target remote diagnosis and care and emergency situations. A unified framework is developed that: (i) provides a diagnostically relevant medical video encoding based on clinical criteria, (ii) enables diagnostically resilient medical video encoding for reliable communications over noisy wireless channels, and (iii) introduces objective and subjective criteria for clinical video quality assessment. The approach is based on a spatially varying encoding scheme, where video slice quantization parameters are varied as a function of diagnostic significance. Video slices are automatically set based on a segmentation algorithm. They are then encoded using a modified version of H.264/AVC flexible macroblock ordering (FMO) technique that allows variable quality slice encoding and redundant slices (RS) for resilience over error prone communication channels.Evaluation of the proposed scheme is performed on a representative collection of ten (10) ultrasound videos, nine of the carotid and one of the femoral arteries, for packet loss rates up to 30%. Extensive simulations incorporating three FMO encoding Andreas Stavrou Panayides – University of Cyprus 2011 methods, different quantization levels and display resolutions, and different packet loss scenarios are investigated. Quality assessment is based on a new clinical rating system that provides for independent evaluations of the different parts of the video (subjective). Objective video quality assessment metrics are also employed and their correlation to the clinical quality assessment of plaque type is derived. To this end, some objective quality assessment measures computed over the plaque video slices gave very good correlations to mean opinion scores (MOS). Here, MOS were computed using two medical experts. Experimental results show that the proposed method achieves enhanced performance in noisy environments, while achieving significant bandwidth demands reductions, providing for transmission over 3G (and beyond) wireless networks. The proposed unified framework can be modified for application to other medical video modalities. This requires the identification of diagnostic ROIs, the adoption of a new clinical diagnostic rating system, and expert validation.

Doctoral Theses