In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with presence surgical instrumentation implants as well soft-tissue resection or deformation. This work investigates similarity metrics in 3D-2D offering improved robustness against mismatch, thereby improving performance reducing eliminating need for manual masking....

Percutaneous screw fixation in pelvic trauma surgery is a challenging procedure that often requires long fluoroscopic exposure times and trial-and-error insertion attempts along narrow bone corridors of the pelvis. We report method to automatically plan surgical trajectories using preoperative CT assist device placement by augmenting scene with planned trajectories. A shape atlas was formed from 40 images used construct statistical model (SSM). Each member included expert definition...

This paper examines MRI analysis of neurodegeneration in Alzheimer's Disease (AD) a network structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing which entorhinal cortex is partitioned into eight subareas. The morphometry markers for three groups subjects (controls, preclinical AD, and symptomatic AD) are indexed to template coordinates measured respect these location timing changes examined subareas as it pertains classic Braak staging...

Spinal screw placement is a challenging task due to small bone corridors and high risk of neurological or vascular complications, benefiting from precision guidance/navigation quality assurance (QA). Implicit both guidance QA the definition surgical plan-i.e. desired trajectories device selection for target vertebrae-conventionally requiring time-consuming manual annotations by skilled surgeon. We propose automation such planning deriving pedicle trajectory patient's preoperative CT MRI. An...

Intraoperative x-ray radiography/fluoroscopy is commonly used to assess the placement of surgical devices in operating room (e.g. spine pedicle screws), but qualitative interpretation can fail reliably detect suboptimal delivery and/or breach adjacent critical structures. We present a 3D-2D image registration method wherein intraoperative radiographs are leveraged combination with prior knowledge patient and components for quantitative assessment device more rigorous quality assurance (QA)...

A multi-stage image-based 3D-2D registration method is presented that maps annotations in a 3D image (e.g. point labels annotating individual vertebrae preoperative CT) to an intraoperative radiograph which the patient has undergone non-rigid anatomical deformation due changes positioning or intervention itself. The proposed (termed msLevelCheck) extends previous rigid solution (LevelCheck) provide accurate mapping of vertebral presence spinal deformation. employs series registrations...

In brain imaging and connectomics, the study of networks, estimating mean a population graphs based on sample is core problem. Often, this problem especially difficult because or cohort size relatively small, sometimes even single subject, while number nodes can be very large with noisy estimates connectivity. While element-wise adjacency matrices common approach, method does not exploit underlying structural properties graphs. We propose using low-rank that incorporates dimension selection...

An algorithm for automatic spinal pedicle screw planning is reported and evaluated in simulation first clinical studies. A statistical atlas of the lumbar spine (N = 40 members) was constructed active shape model (ASM) registration target vertebrae to an unsegmented patient CT. The augmented include 'reference' trajectories through pedicles as defined by a neurosurgeon. Following ASM registration, are transformed CT accumulated define patient-specific trajectory, diameter, length....

To characterize the radiation dose and three-dimensional (3D) imaging performance of a recently developed mobile, isocentric C-arm equipped with flat-panel detector (FPD) for intraoperative cone-beam computed tomography (CBCT) (Cios Spin 3D, Siemens Healthineers) to identify potential improvements in 3D protocols pertinent tasks.The features 30 × cm2 FPD gantry computer-controlled motorization rotation (0-195°), angulation (±220°), height (0-45 cm). Geometric calibration was assessed terms 9...

Decision support to assist in target vertebra localization could provide a useful aid safe and effective spine surgery. Previous solutions have shown 3D-2D registration of preoperative CT intraoperative radiographs reliably annotate vertebral labels for assistance during level localization. We present an algorithm (referred as MR-LevelCheck) perform based on MRI accommodate the increasingly common clinical scenario which is used instead planning. Straightforward adaptation...

Surgical reduction of pelvic dislocation is a challenging procedure with poor long-term prognosis if does not accurately restore natural morphology. The often requires long fluoroscopic exposure times and trial-and-error to achieve accurate reduction. We report method automatically compute the target pose dislocated bones in preoperative CT provide 3D guidance using routine 2D fluoroscopy. A statistical shape model (SSM) (SPM) were formed from an atlas 40 images. Multi-body bone segmentation...

An automatic radiographic labeling algorithm called "LevelCheck" was analyzed as a means of decision support for target localization in spine surgery. The potential clinical utility and scenarios which LevelCheck is likely to be the most beneficial were assessed retrospective data set (398 cases) terms expert consensus from multi-reader study (three surgeons).The aim this evaluate vertebrae localization.Three hundred ninety-eight intraoperative radiographs 178 preoperative computed...

A 3D-2D image registration method is reported for guiding the placement of surgical devices (e.g., K-wires). The solution registers preoperative CT (and planning data therein) to intraoperative radiographs and computes pose, shape, deformation parameters (termed "components") known be in radiographic scene. deformable known-component (dKC-Reg) was applied experiments emulating spine surgery register (K-wires spinal fixation rods) undergoing realistic deformation. two-stage process (i)...

Purpose: Cone-beam computed tomography (CBCT) is commonly used in the operating room to evaluate placement of surgical implants relation critical anatomical structures. A particularly problematic setting, however, imaging metallic implants, where strong artifacts can obscure visualization both implant and surrounding anatomy. Such are compounded when combined with low-dose techniques such as sparse-view acquisition. Approach: This work presents a dual convolutional neural network approach,...

Modern cone-beam CT systems, especially C-arms, are capable of diverse source-detector orbits. However, geometric calibration these systems using conventional configurations spherical fiducials (BBs) may be challenged for novel orbits and system geometries. In part, this is because the BB designed with careful forethought regarding intended orbit so that marker projections do not overlap in projection views. Examples include helical arrangements BBs (Rougee et al 1993 Proc. SPIE 1897 161–9)...

Percutaneous pelvic screw placement is challenging due to narrow bone corridors surrounded by vulnerable structures and difficult visual interpretation of complex anatomical shapes in 2D x-ray projection images. To address these challenges, a system for planning, guidance, quality assurance (QA) presented, providing functionality analogous surgical navigation, but based on robust 3D-2D image registration techniques using fluoroscopy images already acquired routine workflow. Two novel aspects...

Purpose: Data-intensive modeling could provide insight on the broad variability in outcomes spine surgery. Previous studies were limited to analysis of demographic and clinical characteristics. We report an analytic framework called "SpineCloud" that incorporates quantitative features extracted from perioperative images predict surgery outcome. Approach: A retrospective study was conducted which patient demographics, imaging, outcome data collected. Image automatically computed CT....

<strong>Introduction</strong>: Fluoroscopically guided procedures often involve repeated acquisitions for C-arm positioning at the cost of radiation exposure and time in operating room. A virtual fluoroscopy system is reported with potential reducing dose spent positioning, utilizing three key advances: robust 3D-2D registration to a preoperative CT; real-time forward projection on GPU; motorized mobile encoder feedback orientation. <strong>Method</strong>: Geometric calibration was...

Abstract Purpose . A system for long-length intraoperative imaging is reported based on longitudinal motion of an O-arm gantry featuring a multi-slot collimator. We assess the utility tomosynthesis and geometric accuracy 3D image registration surgical guidance evaluation long spinal constructs. Methods collimator with tilted apertures was integrated into imaging. The projective geometry leads to slight view disparity in both projection images (referred as ‘line scans’) ‘slot reconstructions’...

During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown provide a potentially valuable means of decision support in target localization well quality assurance the surgical product. However, robust challenged by mismatch image content between radiographs, arising, for example, anatomical deformation or...

Real-time fusion of magnetic resonance (MR) and ultrasound (US) images could facilitate safe accurate needle placement in spinal interventions. We develop an entirely image-based registration method (independent or complementary to surgical trackers) that includes efficient US probe pose initialization algorithm. The enables the simultaneous display 2D image slices relative 3D pre-procedure MR for navigation. A dictionary-based 3D-2D algorithm was developed which likely positions are...

Motivation/Purpose: This work reports the development and validation of an algorithm to automatically detect localize vertebrae in CT images patients undergoing spine surgery. Slice-by-slice detections using state-of-the art 2D convolutional neural network (CNN) architectures were combined estimate vertebra centroid location 3D including a method that sagittal coronal slices. The solution facilitates applications image guided surgery automatic computation analytics for surgical data science....

For image-guided procedures, the imaging task is often tied to registration of intraoperative and preoperative images a common coordinate system. While accuracy this vital factor in system performance, there relatively little work that relates image quality factors, such as dose, noise, spatial resolution. To create theoretical model for relationship, we present Fisher information approach analyze performance explicit dependence on underlying factors resolution, signal power spectrum. The...

<strong>Purpose</strong>: In image-guided procedures, image acquisition is often performed primarily for the task of geometrically registering information from another dataset, rather than detection / visualization a particular feature. While ability to detect feature in an has been studied extensively with respect quality characteristics (noise, resolution) and ongoing, active area research, comparatively little accomplished relate such registration performance. <strong>Methods</strong>: To...

<strong>Purpose</strong>: Deep-brain stimulation via neuro-endoscopic surgery is a challenging procedure that requires accurate targeting of deep-brain structures can undergo deformations (up to 10 mm). Conventional deformable registration methods have the potential resolve such geometric error between preoperative MR and intraoperative CT but at expense long computation time. New advances in deep learning offer benefits inter-modality image accuracy runtime using novel similarity metrics...