Evidence map›Paper›PMID 37610603›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Arc-to-line frame registration method for ultrasound and photoacoustic image-guided intraoperative robot-assisted laparoscopic prostatectomy.

Hyunwoo Song, Shuojue Yang, Zijian Wu, Hamid Moradi, Russell H Taylor, Jin U Kang, Septimiu E Salcudean, Emad M Boctor

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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 2 countries.

Hyunwoo SongDepartment of Computer Science, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID http://orcid.org/0000-0002-1166-8079
Shuojue YangLaboratory for Computational Sensing and Robotics, The Johns Hopkins University, Baltimore, MD, 21218, USA.
Zijian WuLaboratory for Computational Sensing and Robotics, The Johns Hopkins University, Baltimore, MD, 21218, USA.
Hamid MoradiDepartment of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
Russell H TaylorDepartment of Computer Science, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID http://orcid.org/0000-0001-6272-1100
Jin U KangDepartment of Electrical and Computer Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, 21218, USA.
Septimiu E SalcudeanDepartment of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.ORCID http://orcid.org/0000-0001-8826-8025
Emad M BoctorDepartment of Computer Science, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, 21218, USA. eboctor@jhu.edu.ORCID http://orcid.org/0000-0002-9536-6720
Johns Hopkins University · USUniversity of British Columbia · CA

Funding

CIHR CA Laszlo Chair in Biomedical Engineering held by Professor Salcudean
6 · The paper itself

Abstract

purposeTo achieve effective robot-assisted laparoscopic prostatectomy, the integration of transrectal ultrasound (TRUS) imaging system which is the most widely used imaging modality in prostate imaging is essential. However, manual manipulation of the ultrasound transducer during the procedure will significantly interfere with the surgery. Therefore, we propose an image co-registration algorithm based on a photoacoustic marker (PM) method, where the ultrasound/photoacoustic (US/PA) images can be registered to the endoscopic camera images to ultimately enable the TRUS transducer to automatically track the surgical instrument.

methodsAn optimization-based algorithm is proposed to co-register the images from the two different imaging modalities. The principle of light propagation and an uncertainty in PM detection were assumed in this algorithm to improve the stability and accuracy of the algorithm. The algorithm is validated using the previously developed US/PA image-guided system with a da Vinci surgical robot.

resultsThe target-registration-error (TRE) is measured to evaluate the proposed algorithm. In both simulation and experimental demonstration, the proposed algorithm achieved a sub-centimeter accuracy which is acceptable in practical clinics (i.e., 1.15 ± 0.29 mm from the experimental evaluation). The result is also comparable with our previous approach (i.e., 1.05 ± 0.37 mm), and the proposed method can be implemented with a normal white light stereo camera and does not require highly accurate localization of the PM.

conclusionThe proposed frame registration algorithm enabled a simple yet efficient integration of commercial US/PA imaging system into laparoscopic surgical setting by leveraging the characteristic properties of acoustic wave propagation and laser excitation, contributing to automated US/PA image-guided surgical intervention applications.

Indexed as

LaparoscopyProstatic NeoplasmsRoboticsSurgery, Computer-AssistedAlgorithmsHumansImaging, Three-DimensionalMaleProstatectomyUltrasonographyImage-guided surgical interventionMulti-modality image registrationPhotoacoustic imagingRobot-assisted surgeryUltrasound imaging

Identifiers

PMID37610603
OpenAlexW4386083671

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.