Image-based Registration for a Neurosurgical Robot: Comparison Using Iterative Closest Point and Coherent Point Drift Algorithms

Cutter, Jennifer Ruth; Styles, Iain B.; Leonardis, Ale; Dehghani, Hamid

doi:10.1016/j.procs.2016.07.006

Cited by 7 publications

(8 citation statements)

References 10 publications

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“…For robust matching of clusters with their appropriate codes, the mrbles.Decode class stretches, scales, and rotates the overall cluster pattern to match the original designed code target ratios by implementing an iterative closest point (ICP) matching algorithm [24]. Commonly used in reconstructing 3D surfaces from different scans, such as Computed Tomography (CT), MRI, and optical scans for surgery [25,26], this algorithm minimizes the distances between two clouds of points or between the centroid positions of each cluster in the cloud and the nearest single points (in this case, the ratio cluster centroids and the target code ratios). In the final step, the mrbles.Decode class assigns ICP-transformed LNP ratio clusters (corresponding to unique MRBLE codes) to target code ratios using a Gaussian Mixture Model (GMM, scikit-learn) for supervised classification.…”

Section: Quantifying Bound Fluorescent Materials Via Mrblesextractmentioning

confidence: 99%

An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs)

Harink

Nguyen

Thorn

et al. 2018

Preprint

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< 300 words)Multiplexed bioassays, in which multiple analytes of interest are probed in parallel within a single small volume, have greatly accelerated the pace of biological discovery. Bead-based multiplexed bioassays have many technical advantages, including near solution-phase kinetics, small sample volume requirements, many within-assay replicates to reduce measurement error, and, for some bead materials, the ability to synthesize analytes directly on beads via solid-phase synthesis. To allow bead-based multiplexing, analytes can be synthesized on spectrally encoded beads with a 1:1 linkage between analyte identity and embedded codes. Bead-bound analyte libraries can then be pooled and incubated with a fluorescently-labeled macromolecule of interest, allowing downstream quantification of interactions between the macromolecule and all analytes simultaneously via imaging alone. Extracting quantitative binding data from these images poses several computational image processing challenges, requiring the ability to identify all beads in each image, quantify bound fluorescent material associated with each bead, and determine their embedded spectral code to reveal analyte identities. Here, we present a novel open-source Python software package (the mrbles analysis package) that provides the necessary tools to: (1) find encoded beads in a bright-field microscopy image; (2) quantify bound fluorescent material associated with bead perimeters; (3) identify embedded ratiometric spectral codes within beads; and (4) return data aggregated by embedded code and for each individual bead. We demonstrate the utility of this package by applying it towards analyzing data generated via multiplexed measurement of calcineurin protein binding to MRBLEs (Microspheres with Ratiometric Barcode Lanthanide Encoding) containing known and mutant binding peptide motifs. We anticipate that this flexible package should be applicable to a wide variety of assays, including simple bead or droplet finding analysis, quantification of binding to non-encoded beads, and analysis of multiplexed assays that use ratiometric, spectrally encoded beads.

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Section: Quantifying Bound Fluorescent Materials Via Mrblesextractmentioning

confidence: 99%

An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs)

Harink

Nguyen

Thorn

et al. 2018

Preprint

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“…To realize this, the surgeon collects some landmarks over the anatomical structure surface with the pointer tool and after, these collected points are matched with the virtual model on the 3DSlicer software. In the literature, it was concluded that the iterative closest point algorithm demonstrates a better accuracy in the surface registration outcome [10]. This algorithm consists in paring each collected point from the anatomical structure intraoperatively, with the nearest vertex point of the virtual model.…”

Section: Registrationmentioning

confidence: 99%

Intraoperative bone registration: An implementation in orthopaedic surgery using polaris vicra system

Barbosa

Serrador

Santos

et al. 2017

2017 IEEE 5th Portuguese Meeting on Bioengineering (ENBENG)

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-The introduction of the surgical navigation system in the operating room has brought a great development to the surgeries. Nowadays, the navigated surgeries are present in several fields of medicine. This is a technology that requires an optical tracking system to perform the registration procedure during an intraoperative situation. The preoperative plan consists in performing a 3D reconstruction of the treated region and planning all procedures during the surgery. The registration is an important procedure once it calculates the transformation between the coordinate system of the preoperative plan on the software and the coordinate system of the surgical room in order to be able the visualization of the position and orientation of the surgical instruments in relation to the 3D model obtained in the preoperative plan. A workflow in 3DSlicer software to perform the registration procedure is presented in this paper with all required steps to achieve the navigated surgery. Also, it is presented the results obtained from the registration in order to evaluate the procedure.

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“…During orthopaedic and neurosurgeries, the surgeon has to move the body structures that he is treating. In this case a navigated surgery is needed to track what the surgeon is doing and help him performing the surgery [5]. An accurate registration between the patient and the preoperative images must be made and it would allow the surgeon to move the patient during the surgery to a more convenient position and the surgical plan is adjusted accordingly [5].…”

Section: Registrationmentioning

confidence: 99%

Section: Registrationmentioning

confidence: 99%

“…Cutter et al [5] compares two popular methods of surface registration: iterative closest point (ICP) and coherent point drift (CPD) algorithms. It was verified that ICP results in a better registration [5]. The ICP algorithm consists in pairing each point collected from the physical structure with the nearest point of the virtual model (points in the virtual model can be paired to more than one point of the physical structure), then estimating the transformation that will most reduce the mean square of the distances between pairs.…”

Section: Registrationmentioning

confidence: 99%

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3DSlicer module to perform registration: An intraoperative situation

Barbosa

Serrador

Santos

et al. 2017

2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

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Computer-assisted surgeries (CAS) had a great improvement in last decades. Nowadays, a lot of surgeries are performed with the aid of a tracking system and robotic devices. It is important to ensure the success of the intervention when it is performed with this kind of technologies. One of the most important steps in CAS is registration that allows the surgeon to track his instruments and to know what he is doing when the surgical field of view is limited. A 3DSlicer module is presented to perform the registration procedure quickly and intuitively, since this step must be made as fast as possible. This module allows the surgeon to collect points from the patient's anatomical structure that he is working on in order to perform a point-to-point registration followed by the surface registration based on iterative closest point algorithm. Thus, it is possible to match the coordinates system of the 3DSlicer model and the coordinates system of operating room so that the preoperative 3D model on the software and the tracking of the surgical instruments used during the surgery are synchronized. An example using a sheep skull and a tracking system is described and the results of the registration are shown. The registration procedure is evaluated calculating the mean distance from the landmarks from patient's anatomical structure and the surface of the 3DSlicer model. The value obtained was 0,29 mm RMS which indicates that the module could be a good option to perform the registration in a surgical room.

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Image-based Registration for a Neurosurgical Robot: Comparison Using Iterative Closest Point and Coherent Point Drift Algorithms

Cited by 7 publications

References 10 publications

An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs)

An open-source software analysis package for Microspheres with Ratiometric Barcode Lanthanide Encoding (MRBLEs)

Intraoperative bone registration: An implementation in orthopaedic surgery using polaris vicra system

3DSlicer module to perform registration: An intraoperative situation

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