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Abstract. In this work, we address the problem of automated measurement of the interventricular septum thickness, one of the key parameters in cardiology, from B-mode echocardiograms. The problem is challenging due to high levels of noise, multi modal intensity, weak contrast due to near field haze, and non rigid motion of the septum across frames. We introduce a complete system for automated measurement of septum thickness from B-mode echocardiograms incorporating three main components: a 1D curve evolution algorithm using region statistics for segmenting the septum, a motion clustering method to locate the mitral valve, and a robust method to calculate the septum width from these inputs in accordance with medical standards. Our method effectively handles the challenges of such measurements and runs in near real time. Results on 57 patient recordings showed excellent agreement of the automated measurements with expert manual measurements.

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Aim To determine the role of levator ani trauma in anal incontinence (AI), whilst controlling for anal sphincter injury. Methods The records of 1273 patients who had attended a tertiary urogynaecology unit between 1st of January to 31st December 2016 were reviewed. AI was assessed using St Mark's score and visual analogue scale (VAS). Levator muscle and anal sphincter trauma were examined by translabial ultrasound using tomographic imaging, with archived data sets investigated blinded against all clinical data. A complete avulsion was diagnosed if at least three central tomographic slices showed an abnormal muscle insertion, rated separately for each side. A significant anal sphincter defect was diagnosed if at least four out of six slices showed a defect of ≥ 30°. Results Avulsion was associated with St Mark's score (P = 0.005) and VAS bother of AI (P = 0.022) both on univariate analysis and when controlling for external anal sphincter (EAS) trauma on translabial imaging, forceps, body mass index (BMI) and age (P = 0.011 and P = 0.04, respectively). AI expressed as a binary variable was significantly associated with avulsion on univariate analysis (P = 0.011), although the association became nonsignificant after controlling for anal sphincter trauma, age, BMI and forceps delivery (P = 0.084). Conclusion In this retrospective observational study, we found a weak association between levator ani avulsion and measures of AI, which largely remained significant when controlling for anal sphincter trauma. However, given the large data set, any clinical effect of levator trauma on AI is likely to be minor.

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Abstract. Automated robust segmentation of intra-ventricular septum (IVS) from B-mode echocardiographic images is an enabler for early quantification of cardiac disease. Segmentation of septum from ultrasound images is very challenging due to variations in intensity/contrast in and around the septum, speckle noise and non-rigid shape variations of the septum boundary. In this work, we effectively address these challenges using an approach that merges novel computer vision ideas with physiological markers present in cardiac scans. Specifically, we contribute towards the following: 1) A novel 1-D active contour segmentation approach that utilizes non-local (NL) temporal cues, 2) Robust initialization of the active contour framework, based on NL-means de-noising, and MRF based clustering that incorporates physiological cues. We validate our claims using cardiac measurement results on ∼30 cardiac scan videos (∼2000 ultrasound frames in total). Our method is fully automatic and near real time ( 0.1sec/frame) implementation.

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