A Pipeline for Volume Electron Microscopy of the Caenorhabditis elegans Nervous System.

The "connectome," a comprehensive wiring diagram of synaptic connectivity, is achieved through volume electron microscopy (vEM) analysis of an entire nervous system and all associated non-neuronal tissues. White et al. (1986) pioneered the fully manual reconstruction of a connectome using Caenorhabditis elegans. Recent advances in vEM allow mapping new C. elegans connectomes with increased throughput, and reduced subjectivity. Current vEM studies aim to not only fill the remaining gaps in the original connectome, but also address fundamental questions including how the connectome changes during development, the nature of individuality, sexual dimorphism, and how genetic and environmental factors regulate connectivity. Here we describe our current vEM pipeline and projected improvements for the study of the C. elegans nervous system and beyond

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

MRI evidence for altered venous drainage and intracranial compliance in mild traumatic brain injury.

To compare venous drainage patterns and associated intracranial hydrodynamics between subjects who experienced mild traumatic brain injury (mTBI) and age- and gender-matched controls. Thirty adult subjects (15 with mTBI and 15 age- and gender-matched controls) were investigated using a 3T MR scanner. Time since trauma was 0.5 to 29 years (mean 11.4 years). A 2D-time-of-flight MR-venography of the upper neck was performed to visualize the cervical venous vasculature. Cerebral venous drainage through primary and secondary channels, and intracranial compliance index and pressure were derived using cine-phase contrast imaging of the cerebral arterial inflow, venous outflow, and the craniospinal CSF flow. The intracranial compliance index is the defined as the ratio of maximal intracranial volume and pressure changes during the cardiac cycle. MR estimated ICP was then obtained through the inverse relationship between compliance and ICP. Compared to the controls, subjects with mTBI demonstrated a significantly smaller percentage of venous outflow through internal jugular veins (60.9±21% vs. controls: 76.8±10%; p = 0.01) compensated by an increased drainage through secondary veins (12.3±10.9% vs. 5.5±3.3%; p<0.03). Mean intracranial compliance index was significantly lower in the mTBI cohort (5.8±1.4 vs. controls 8.4±1.9; p<0.0007). Consequently, MR estimate of intracranial pressure was significantly higher in the mTBI cohort (12.5±2.9 mmHg vs. 8.8±2.0 mmHg; p<0.0007). mTBI is associated with increased venous drainage through secondary pathways. This reflects higher outflow impedance, which may explain the finding of reduced intracranial compliance. These results suggest that hemodynamic and hydrodynamic changes following mTBI persist even in the absence of clinical symptoms and abnormal findings in conventional MR imaging

Patient specific numerical simulation of flow in the human upper airways for assessing the effect of nasal surgery

The study is looking into the potential of using computational fluid dynamics (CFD) as a tool for predicting the outcome of surgery for alleviation of obstructive sleep apnea syndrome (OSAS). From pre- and post-operative computed tomography (CT) of an OSAS patient, the pre- and post-operative geometries of the patient's upper airways were generated. CFD simulations of laminar flow in the patient's upper airway show that after nasal surgery the mass flow is more evenly distributed between the two nasal cavities and the pressure drop over the nasal cavity has increased. The pressure change is contrary to clinical measurements that the CFD results have been compared with, and this is most likely related to the earlier steps of modelling - CT acquisition and geometry retrieval.Comment: Proceedings of the 12th International Conference on CFD in Oil & Gas, Metallurgical and Process Industries, Trondheim, Norway, May 30th - June 1st, 2017, 11 pages, 13 figure

Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

Three dimensional quantification of soil hydraulic properties using X-ray Computed Tomography and image based modelling

We demonstrate the application of a high-resolution X-ray Computed Tomography (CT) method to quantify water distribution in soil pores under successive reductive drying. We focus on the wet end of the water release characteristic (WRC) (0 to -75 kPa) to investigate changes in soil water distribution in contrasting soil textures (sand and clay) and structures (sieved and field structured), to determine the impact of soil structure on hydraulic behaviour. The 3D structure of each soil was obtained from the CT images (at a 10 µm resolution). Stokes equations for flow were solved computationally for each measured structure to estimate hydraulic conductivity. The simulated values obtained compared extremely well with the measured saturated hydraulic conductivity values. By considering different sample sizes we were able to identify that the smallest possible representative sample size which is required to determine a globally valid hydraulic conductivity