Multi-view Contour-constrained Transformer Network for Thin-cap Fibroatheroma Identification

Identification and detection of thin-cap fibroatheroma (TCFA) from intravascular optical coherence tomography (IVOCT) images is critical for treatment of coronary heart diseases. Recently, deep learning methods have shown promising successes in TCFA identification. However, most methods usually do not effectively utilize multi-view...

Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images

Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and...

Towards quantitative digital subtraction perfusion angiography: An animal study

Background: X-ray digital subtraction angiography (DSA) is the imaging modality for peri-procedural guidance and treatment evaluation in (neuro-) vascular interventions. Perfusion image construction from DSA, as a means of quantitatively depicting cerebral hemodynamics, has been shown feasible. However, the quantitative property of perfusion...

Multimodal markers for technology-independent integration of augmented reality devices and surgical navigation systems

Augmented reality (AR) permits the visualization of pre-operative data in the surgical field of view of the surgeon. This requires the alignment of the AR device’s coordinate system with the used navigation/tracking system. We propose a multimodal marker approach to align an AR device with a tracking system: in our implementation, an...

Augmented reality navigation for minimally invasive craniosynostosis surgery: a phantom study

Purpose: In minimally invasive spring-assisted craniectomy, surgeons plan the surgery by manually locating the cranial sutures. However, this approach is prone to error. Augmented reality (AR) could be used to visualize the cranial sutures and assist in the surgery planning. The purpose of our work is to develop an AR-based system to...

Evaluation of Marker Tracking Using Mono and Stereo Vision in Microsoft HoloLens for Surgical Navigation

Optical-based navigation systems are widely used in surgical interventions. However, despite their great utility and accuracy, they are expensive and require time and effort to setup for surgeries. Moreover, traditional navigation systems use 2D screens to display instrument positions causing the surgeons to look away from the operative field...

Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy

Intracranial vessel perforation is a peri-procedural complication during endovascular therapy (EVT). Prompt recognition is important as its occurrence is strongly associated with unfavorable treatment outcomes. However, perforations can be hard to detect because they are rare, can be subtle, and the interventionalist is working under time...

Time dependency of automated collateral scores in computed tomography angiography and computed tomography perfusion images in patients with intracranial arterial occlusion

Purpose: The assessment of collateral status may depend on the timing of image acquisition. The purpose of this study is to investigate whether there are optimal time points in CT Perfusion (CTP) for collateral status assessment, and compare collaterals scores at these time points with collateral scores from multiphase CT angiography (mCTA)....

AR-Assisted Craniotomy Planning for Tumour Resection

Craniotomy is a procedure where neurosurgeons open the patient’s skull to gain direct access to the brain. The craniotomy’s position defines the access path from the skull surface to the tumour and, consequently, the healthy brain tissue to be removed to reach the tumour. This is a complex procedure where a neurosurgeon is required to...

Block-matching-based registration to evaluate ultrasound visibility of percutaneous needles in liver-mimicking phantoms

Purpose: To present a novel methodical approach to compare visibility of percutaneous needles in ultrasound images. Methods: A motor-driven rotation platform was used to gradually change the needle angle while capturing image data. Data analysis was automated using block-matching-based registration, with a tracking and refinement step. Every...

Region based level set segmentation of the outer wall of the carotid bifurcation in CTA

This paper presents a level set based method for segmenting the outer vessel wall and plaque components of the carotid artery in CTA. The method employs a GentleBoost classification framework that classifies pixels as calcified region or not, and inside or outside the vessel wall. The combined result of both classifications is used to construct...

Multispectral MRI centerline tracking in carotid arteries

We propose a minimum cost path approach to track the centerlines of the internal and external carotid arteries in multispectral MR data. User interaction is limited to the annotation of three seed points. The cost image is based on both a measure of vessel medialness and lumen intensity similarity in two MRA image sequences: Black Blood MRA and...

A patient-specific visualization tool for comprehensive analysis of coronary CTA and perfusion MRI data

Cardiac magnetic resonance perfusion imaging (CMR) and computed tomography angiography (CTA) are widely used to assess heart disease. CMR is used to measure the global and regional myocardial function and to evaluate the presence of ischemia; CTA is used for diagnosing coronary artery disease, such as coronary stenoses. Nowadays, the hemodynamic...

Correspondence free 3D statistical shape model fitting to sparse X-ray projections

Fully automatic cardiac segmentation from 3D CTA data: A multi-atlas based approach

Selective visualization on curvilinear grids, Selectieve visualisatie op kromlijnige roosters