Toward ICE-XRF fusion: real-time pose estimation of the intracardiac echo probe in 2D X-ray using deep learning.

Purpose: Valvular heart disease affects 2.5% of the general population and 10% of people aged over 75, with many patients untreated due to high surgical risks. Transcatheter valve therapies offer a safer, less invasive alternative but rely on ultrasound and X-ray image guidance.

Cerebral Artery and Vein Segmentation in Four-dimensional CT Angiography Using Convolutional Neural Networks.

Purpose: To implement and test a deep learning approach for the segmentation of the arterial and venous cerebral vasculature with four-dimensional (4D) CT angiography.

Materials And Methods: Patients who had undergone 4D CT angiography for the suspicion of acute ischemic stroke were retrospectively identified. A total of 390 patients evaluated in 2014 ( = 113) or 2018 ( = 277) were included in this study, with each patient having undergone one 4D CT angiographic scan.

Image-level detection of arterial occlusions in 4D-CTA of acute stroke patients using deep learning.

The triage of acute stroke patients is increasingly dependent on four-dimensional CTA (4D-CTA) imaging. In this work, we present a convolutional neural network (CNN) for image-level detection of intracranial anterior circulation artery occlusions in 4D-CTA. The method uses a normalized 3D time-to-signal (TTS) representation of the input image, which is sensitive to differences in the global arrival times caused by the potential presence of vascular pathologies.

Circle of Willis Collateral Flow in Carotid Artery Occlusion Is Depicted by 4D-CTA.

Background: In case of carotid artery occlusion, the risk and extent of ischemic cerebral damage are highly dependent on the pathways of collateral flow including the anatomy of the circle of Willis. In this report, cases are presented to illustrate that 4-dimensional computed tomography angiography (4D-CTA) can be considered as a noninvasive alternative to digital subtraction angiography for the evaluation of circle of Willis collateral flow.

Case Description: Five patients with unilateral internal carotid artery (ICA) occlusion underwent 4D-CTA for the evaluation of intracranial hemodynamics.

Robust Segmentation of the Full Cerebral Vasculature in 4D CT of Suspected Stroke Patients.

A robust method is presented for the segmentation of the full cerebral vasculature in 4-dimensional (4D) computed tomography (CT). The method consists of candidate vessel selection, feature extraction, random forest classification and postprocessing. Image features include among others the weighted temporal variance image and parameters, including entropy, of an intensity histogram in a local region at different scales.

Automated multistructure atlas-assisted detection of lymph nodes using pelvic MR lymphography in prostate cancer patients.

Purpose: To investigate whether atlas-based anatomical information can improve a fully automated lymph node detection system for pelvic MR lymphography (MRL) images of patients with prostate cancer.

Methods: Their data set contained MRL images of 240 prostate cancer patients who had an MRL as part of their clinical work-up between January 2008 and April 2010, with ferumoxtran-10 as contrast agent. Each MRL consisted of at least a 3D T1-weighted sequence, a 3D T2*-weighted sequence, and a FLASH-3D sequence.

Analysis of perfusion MRI in stroke: To deconvolve, or not to deconvolve.

Purpose: There is currently controversy regarding the benefits of deconvolution-based parameters in stroke imaging, with studies suggesting a similar infarct prediction using summary parameters. We investigate here the performance of deconvolution-based parameters and summary parameters for dynamic-susceptibility contrast (DSC) MRI analysis, with particular emphasis on precision.

Methods: Numerical simulations were used to assess the contribution of noise and arterial input function (AIF) variability to measurement precision.