An Effective Ultrasound Video Communication System Using Despeckle Filtering and HEVC

The recent emergence of the high-efficiency video coding (HEVC) standard promises to deliver significant bitrate savings over current and prior video compression standards, while also supporting higher resolutions that can meet the clinical acquisition spatiotemporal settings. The effective application of HEVC to medical ultrasound necessitates a careful evaluation of strict clinical criteria that guarantee that clinical quality will not be sacrificed in the compression process. Furthermore, the potential use of despeckle filtering prior to compression provides for the possibility of significant additional bitrate savings that have not been previously considered. This paper provides a thorough comparison of the use of MPEG-2, H.263, MPEG-4, H.264/AVC, and HEVC for compressing atherosclerotic plaque ultrasound videos. For the comparisons, we use both subjective and objective criteria based on plaque structure and motion. For comparable clinical video quality, experimental evaluation on ten videos demonstrates that HEVC reduces bitrate requirements by as much as 33.2% compared to H.264/AVC and up to 71% compared to MPEG-2. The use of despeckle filtering prior to compression is also investigated as a method that can reduce bitrate requirements through the removal of higher frequency components without sacrificing clinical quality. Based on the use of three despeckle filtering methods with both H.264/AVC and HEVC, we find that prior filtering can yield additional significant bitrate savings. The best performing despeckle filter (DsFlsmv) achieves bitrate savings of 43.6% and 39.2% compared to standard nonfiltered HEVC and H.264/AVC encoding, respectively

A Review of Error Resilience Techniques in Video Streaming

Abstract-Delivering video data of satisfactory quality over unreliable networks -such as the internet or wireless networks -is a demanding area which has received significant attention of the research community over the past few years. Given the fact that packet loss is inevitable and therefore the presence of errors granted, the effort is directed towards limiting the effect of these errors. A number of techniques have been developed to address this issue. This paper aims to summarize the most significant approaches for: error resilience, error concealment and joint encoder-decoder error control techniques, and to provide a thorough discussion of the benefits and drawbacks of these error control methods. Furthermore, two case studies of error resilience utilization are presented, namely Ad-hoc networks and Multimedia Broadcast Multiple Services (MBMS)

Proposal of Real-Time Echocardiogram Transmission Based on Visualization Modes with WiMAX Access

This study presents a new approach to improve the echocardiogram transmissions over WiMAX networks. Using a compression method based on visualization modes and a reliable method that adapts to the channel conditions, overall performance results are improved compared to classical approaches. The echocardiogram transmission using a compression method based on visualization modes requires lower bandwidth than without considering visualization modes. Furthermore, if the proposed reliability method is also used, the echocardiogram is more often visualized with adequate clinical quality than compressing the echocardiogram without distinguishing the visualization modes and without using a reliability method for the available dataset. The reduction in the bandwidth ranges from 29 kbps to 166 kbps for the simulated scenarios. 1

Quantitative MRI Brain Studies in Mild Cognitive Impairment and Alzheimer's disease: A Methodological Review

Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging especially in Mild Cognitive Impairment (MCI) subjects. Quantitative structural Magnetic Resonance Imaging (MRI) acquisition methods in combination with Computer-Aided Diagnosis (CAD) are currently being used for the assessment AD. These acquisitions methods include: i) Voxel-based Morphometry (VBM), ii) volumetric measurements in specific Regions of Interest (ROIs), iii) cortical thickness measurements, iv) shape analysis and v) texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following 3 groups: Normal Controls (NC), MCI and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the Medial Temporal Lobe (MTL) especially in the entorhinal cortex, whereas with disease progression both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus

An overview of quantitative magnetic resonance imaging analysis studies in the assessment of alzheimer’s disease

Medical image analysis and visualization, can contribute in quantitative and qualitative analysis of Magnetic Resonance Imaging (MRI) towards an earlier diagnosis of Alzheimer’s disease (AD). Moreover, the early detection of Mild Cognitive Impairment (MCI) has recently attracted a lot of attention. The main objective of this paper is to present a survey of recent key papers focused on the classification of MCI and AD and the prediction of conversion from MCI to AD using volume, shape and texture analysis. The most frequent anatomical features used in the assessment of AD, is the hippocampus, the cortex and the local concentration of grey matter. Shape analysis can identify the signs of early hippocampal atrophy, whereas volume analysis evaluates the structure as a whole. Shape analysis seems to be a more accurate technique both in classification of patients and in prognostic prediction. Compared to volume, shape and voxel based morphometry (VBM) techniques, texture analysis can be used to identify the microstructural changes before the larger-scale morphological characteristics which are detected by the other aforementioned techniques. We concluded that quantitative MRI measurements can be used as an in vivo surrogate for the classification of patients and furthermore, for the tracking the Alzheimer’s disease progression

Hippocampal and entorhinal cortex volume changes in Alzheimer's disease patients and mild cognitive impairment subjects.

Hippocampal and entorhinal cortex as scanned in Magnetic Resonance Imaging (MRI), are two of the most commonly used Regions of Interest (ROIs) for the assessment of Alzheimer’s disease (AD). Both structures are used for the classification between Normal Controls (NC), Mild Cognitive Impairment (MCI) and AD subjects and for the disease prognosis. The objective of this study was to evaluate how the volume of these two structures changes between the following groups: NC vs AD, NC vs MCI, MCI vs MCI converters (MCIc - subjects who had converted to AD within 48 months), and AD vs MCIc subjects. Both structures were significantly reduced in volume for MCIc and AD subjects compared to NC. For both MCI and MCIc groups, the atrophy rate was correlated for both structures. In AD subjects, entorhinal cortex was more affected by atrophy. In conclusion, structural MRI and volumetric measurements of the hippocampus and entorhinal cortex can be used as early signs for the assessment of AD, and this is in agreement with previous studies

Fast Localization of Optic Disc and Fovea in Retinal Images for Eye Disease Screening

ABSTRACT Optic disc (OD) and fovea locations are two important anatomical landmarks in automated analysis of retinal disease in color fundus photographs. This paper presents a new, fast, fully automatic optic disc and fovea localization algorithm developed for diabetic retinopathy (DR) screening. The optic disc localization methodology comprises of two steps. First, the OD location is identified using template matching and directional matched filter. To reduce false positives due to bright areas of pathology, we exploit vessel characteristics inside the optic disc. The location of the fovea is estimated as the point of lowest matched filter response within a search area determined by the optic disc location. Second, optic disc segmentation is performed. Based on the detected optic disc location, a fast hybrid level-set algorithm which combines the region information and edge gradient to drive the curve evolution is used to segment the optic disc boundary. Extensive evaluation was performed on 1200 images (Messidor) composed of 540 images of healthy retinas, 431 images with DR but no risk of macular edema (ME), and 229 images with DR and risk of ME. The OD location methodology obtained 98.3% success rate, while fovea location achieved 95% success rate. The average mean absolute distance (MAD) between the OD segmentation algorithm and "gold standard" is 10.5% of estimated OD radius. Qualitatively, 97% of the images achieved Excellent to Fair performance for OD segmentation. The segmentation algorithm performs well even on blurred images

Corrigendum: Assessment of Alzheimer's Disease Based on Texture Analysis of the Entorhinal Cortex

[This corrects the article DOI: 10.3389/fnagi.2020.00176.]