AM-FM Texture Image Analysis of the Intima and Media Layers of the Carotid Artery

Abstract. The purpose of this paper is to propose the use of amplitude modulation-frequency modulation (AM-FM) features for describing atherosclerotic plaque features that are associated with clinical factors such as intima media thickness and a patient's age. AM-FM analysis reveals the instantaneous amplitude (IA) of the media layer decreases with age. This decrease in IA maybe attributed to the reduction in calcified, stable plaque components and an increase in stroke risk with age. On the other hand, an increase in the median instantaneous frequency (IF) of the media layer suggests the fragmentation of solid, large plaque components, which also lead to an increase in the risk of stroke. The findings suggest that AM-FM features can be used to assess the risk of stroke over a wide range of patient populations. Future work will incorporate a new texture image retrieval system that uses AM-FM features to retrieve intima and intima media layer images that could be associated with the same level of the risk of stroke

Carotid Ultrasound Boundary Study (CUBS): An Open Multicenter Analysis of Computerized Intima–Media Thickness Measurement Systems and Their Clinical Impact

[Abstract] Common carotid intima–media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement and their clinical impacts on the same patient data set is lacking. Here we compared and assessed five computerized CIMT algorithms against three expert analysts’ manual measurements on a data set of 1088 patients from two centers. Inter- and intra-observer variability was assessed, and the computerized CIMT values were compared with those manually obtained. The CIMT measurements were used to assess the correlation with clinical parameters, cardiovascular event prediction through a generalized linear model and the Kaplan–Meier hazard ratio. CIMT measurements obtained with a skilled analyst's segmentation and the computerized segmentation were comparable in statistical analyses, suggesting they can be used interchangeably for CIMT quantification and clinical outcome investigation. To facilitate future studies, the entire data set used is made publicly available for the community at http://dx.doi.org/10.17632/fpv535fss7.

A functional variant in NEPH3 gene confers high risk of renal failure in primary hematuric glomerulopathies. Evidence for predisposition to microalbuminuria in the general population.

BACKGROUND: Recent data emphasize that thin basement membrane nephropathy (TBMN) should not be viewed as a form of benign familial hematuria since chronic renal failure (CRF) and even end-stage renal disease (ESRD), is a possible development for a subset of patients on long-term follow-up, through the onset of focal and segmental glomerulosclerosis (FSGS). We hypothesize that genetic modifiers may explain this variability of symptoms. METHODS: We looked in silico for potentially deleterious functional SNPs, using very strict criteria, in all the genes significantly expressed in the slit diaphragm (SD). Two variants were genotyped in a cohort of well-studied adult TBMN patients from 19 Greek-Cypriot families, with a homogeneous genetic background. Patients were categorized as "Severe" or "Mild", based on the presence or not of proteinuria, CRF and ESRD. A larger pooled cohort (HEMATURIA) of 524 patients, including IgA nephropathy patients, was used for verification. Additionally, three large general population cohorts [Framingham Heart Study (FHS), KORAF4 and SAPHIR] were used to investigate if the NEPH3-V353M variant has any renal effect in the general population. RESULTS AND CONCLUSIONS: Genotyping for two high-scored variants in 103 TBMN adult patients with founder mutations who were classified as mildly or severely affected, pointed to an association with variant NEPH3-V353M (filtrin). This promising result prompted testing in the larger pooled cohort (HEMATURIA), indicating an association of the 353M variant with disease severity under the dominant model (p = 3.0x10-3, OR = 6.64 adjusting for gender/age; allelic association: p = 4.2x10-3 adjusting for patients' kinships). Subsequently, genotyping 6,531 subjects of the Framingham Heart Study (FHS) revealed an association of the homozygous 353M/M genotype with microalbuminuria (p = 1.0x10-3). Two further general population cohorts, KORAF4 and SAPHIR confirmed the association, and a meta-analysis of all three cohorts (11,258 individuals) was highly significant (p = 1.3x10-5, OR = 7.46). Functional studies showed that Neph3 homodimerization and Neph3-Nephrin heterodimerization are disturbed by variant 353M. Additionally, 353M was associated with differential activation of the unfolded protein response pathway, when overexpressed in stressed cultured undifferentiated podocyte cells, thus attesting to its functional significance. Genetics and functional studies support a "rare variant-strong effect" role for NEPH3-V353M, by exerting a negative modifier effect on primary glomerular hematuria. Additionally, genetics studies provide evidence for a role in predisposing homozygous subjects of the general population to micro-albuminuria

Ultrasound image analysis of the carotid artery

Stroke is one of the most important causes of death in the world and the leading cause of serious, long-term disability. There is an urgent need for better techniques to diagnose patients at risk of stroke based on the measurements of the intima media thickness (IMT) and the segmentation of the atherosclerotic carotid plaque. The objective of this work was to carry out a comparative evaluation of despeckle filtering on ultrasound images of the carotid artery, and develop a new segmentation system, for detecting the IMT of the common carotid artery and the borders of the athrerosclerotic carotid plaque in longitudinal ultrasound images of the carotid artery. To the best of our knowledge no similar system has been developed for segmenting the atherosclerotic carotid plaque, although a number of techniques have been proposed for IMT segmentation. A total of 11 despeckle filtering methods were evaluated based on texture analysis, image quality evaluation metrics, and visual evaluation made by two experts, on 440 ultrasound images of the carotid artery bifurcation. Furthermore, the proposed IMT and plaque segmentation techniques were evaluated on 100 and 80 longitudinal ultrasound images of the carotid bifurcation respectively based on receiver operating chatracteristic (ROC) analysis. The despeckle filtering results showed that a despeckle filter based on local statistics (lsmv) improved the class separation between asymptomatic and symptomatic classes, gave only a marginal improvement in the percentage of correct classifications success rate, and improved the visual assessment carried out by the experts. It was also found that the lsmv despeckle filter can be used for despeckling asymptomatic images where the expert is interested mainly in the plaque composition and texture analysis, whereas a geometric despeckle filter (gf4d) can be used for despeckling of symptomatic images where the expert is interested in identifying the degree of stenosis and the plaque borders. The IMT snakes segmentation results showed that no significant difference was found between the manual and the snakes segmentation measurements. Better segmentation results were obtained for the normalized despeckled images. The plaque segmentation results showed that, the Lai&Chin snakes segmentation method gives results comparable to the manual delineation procedure. The IMT and plaque snakes segmentation method may be therefore used to complement and assist the final expert’s evaluation. The proposed despeckling and segmentation methods will be further evaluated on a larger number of ultrasound images and on multiple experts’ evaluation. Furthermore, it is expected that both methods will be incorporated into an integrated system enabling the texture analysis of the segmented plaque, providing an automated system for the early diagnosis and the assessment of the risk of stroke

An automated integrated speech and face imageanalysis system for the identification of human emotions

Objective: Human interactions are related to speech and facial characteristics. It was suggested that speech signals and/or images of facial expressions may reveal human emotions and that both interact for the verification of a person's identity. The present study proposes and evaluates an automated integrated speech signal and facial image analysis system for the identification of seven different human emotions (Normal (N), Happy (H), Sad (S), Disgust (D), Fear (F), Anger (A), and Surprise (Su)). Methods: Speech recordings and face images from 7,441 subjects aged 20≤age≤74 were collected, normalized and filtered. From all the above recordings 55 speech signal features and 61 different image face texture features were extracted. Statistical and model multi-classification analysis were performed to select the features able to statistically significantly distinguish between the seven aforementioned human emotions (N, H, S, D, F, A and Su). The selected features alone or a combination of these features along with age and gender of the sample investigated were used to build two learning-based classifiers; and the classifiers’ accuracy was computed. Results: For each of the above mentioned human emotions, statistical significantly different speech and face image features were identified that may be used to distinguish between the aforementioned groups (N vs H, N vs S, N vs D, N vs F, N vs A, N vs Su). Using solely the statistically significant speech and image features identified, an overall percentage of correct classification (%CC) score of 93% was achieved. Conclusions: A significant number of speech and face image features have been derived from continuous speech and face images. Features were identified that were able to identify between seven different emotional human states. This study poses the basis for the development of an integrated system for the identification of emotional states from automatic analysis of free speech and image face analysis. Future work will investigate the development and integration of the proposed method into a mobile device

Ultrasound Image Analysis of The Carotid Artery: Applications in ultrasound filtering, segmentation and texture analysis

Stroke is one of the most important causes of death in the world and the leading cause of serious, long-term disability. There is an urgent need for better techniques to diagnose patients at risk of stroke based on the measurements of the intima media thickness (IMT) and the segmentation of the atherosclerotic carotid plaque. The objective of this work was to carry out a comparative evaluation of despeckle filtering on ultrasound images of the carotid artery, and develop a new segmentation system, for detecting the IMT of the common carotid artery and the borders of the athrerosclerotic carotid plaque in longitudinal ultrasound images of the carotid artery. The proposed methods were evaluated on a large number of ultrasound images and on multiple experts’ evaluation. Furthermore, it is expected that the propose methods will be incorporated into an integrated system enabling the texture analysis of the segmented plaque, providing an automated system for the early diagnosis diagnosis and the assessment of the risk of stroke

A review of ultrasound common carotid artery image and video segmentation techniques

The determination of the wall thickness [intima-media thickness (IMT)], the delineation of the atherosclerotic carotid plaque, the measurement of the diameter in the common carotid artery (CCA), as well as the grading of its stenosis are important for the evaluation of the atherosclerosis disease. All these measurements are also considered to be significant markers for the clinical evaluation of the risk of stroke. A number of CCA segmentation techniques have been proposed in the last few years either for the segmentation of the intima-media complex (IMC), the lumen of the CCA, or for the atherosclerotic carotid plaque from ultrasound images or videos of the CCA. The present review study proposes and discusses the methods and systems introduced so far in the literature for performing automated or semi-automated segmentation in ultrasound images or videos of the CCA. These are based on edge detection, active contours, level sets, dynamic programming, local statistics, Hough transform, statistical modeling, neural networks, and an integration of the above methods. Furthermore, the performance of these systems is evaluated and discussed based on various evaluation metrics. We finally propose the best performing method that can be used for the segmentation of the IMC and the atherosclerotic carotid plaque in ultrasound images and videos. We end the present review study with a discussion of the different image and video CCA segmentation techniques, future perspectives, and further extension of these techniques to ultrasound video segmentation and wall tracking of the CCA. Future work on the segmentation of the CCA will be focused on the development of integrated segmentation systems for the complete segmentation of the CCA as well as the segmentation and motion analysis of the plaque and or the IMC from ultrasound video sequences of the CCA. These systems will improve the evaluation, follow up, and treatment of patients affected by advanced atherosclerosis disease conditions

Ultrasound image analysis of the carotid artery

Stroke is one of the most important causes of death in the world and the leading cause of serious, long-term disability. There is an urgent need for better techniques to diagnose patients at risk of stroke based on the measurements of the intima media thickness (IMT) and the segmentation of the atherosclerotic carotid plaque. The objective of this work was to carry out a comparative evaluation of despeckle filtering on ultrasound images of the carotid artery, and develop a new segmentation system, for detecting the IMT of the common carotid artery and the borders of the athrerosclerotic carotid plaque in longitudinal ultrasound images of the carotid artery. To the, best of our knowledge no similar system has been developed for segmenting the atherosclerotic carotid plaque, although a number of techniques have been proposed for IMT segmentation. A total of 11 despeckle filtering methods were evaluated based on texture analysis, image quality evaluation metrics, and visual evaluation made by two experts, on 440 ultrasound images of the carotid artery bifurcation. Furthermore, the proposed IMT and plaque segmentation techniques were evaluated on 100 and 80 longitudinal ultrasound images of the carotid bifurcation respectively based on receiver operating chatracteristic (ROC) analysis. The despeckle filtering results showed that a despeckle filter based on local statistics (lsmv) improved the class separation between asymptomatic and symptomatic classes, gave only a marginal improvement in the percentage of correct classifications success rate, and improved the visual assessment carried out by the experts. It was also found that the lsmv despeckle filter can be used for despeckling asymptomatic images where the expert is interested mainly in the plaque composition and texture analysis, whereas a geometric despeckle filter (gf4d) can be used for despeckling of symptomatic images where the expert is interested in identifying the degree of stenosis and the plaque borders. The IMT snakes segmentation results showed that no significant difference was found between the manual and the snakes segmentation measurements. Better segmentation results were obtained for the normalized despeckled images. The plaque segmentation, results showed that, the Lai & Chin snakes segmentation method gives results comparable to the manual delineation procedure. The IMT and plaque snakes segmentation method may be therefore used to complement and assist the final expert's evaluation. The proposed despeckling and segmentation methods will be further evaluated on a larger number of ultrasound images and on multiple experts' evaluation. Furthermore, it is expected that both methods will be incorporated into an integrated system enabling the texture analysis of the segmented plaque, providing an automated system for the early diagnosis and the assessment of the risk of stroke