Dataset Information

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation.

ABSTRACT: Tactile sensory input of surgeons is severely limited in minimally invasive surgery, therefore manual palpation cannot be performed for intraoperative tumor detection. Computer-aided palpation, in which tactile information is acquired by devices and relayed to the surgeon, is one solution for overcoming this limitation. An important design factor is the method by which the acquired information is fed back to the surgeon. However, currently there is no systematic method for achieving this aim, and it is possible that a badly implemented feedback mechanism could adversely affect the performance of the surgeon. In this study, we propose an assistance algorithm for intraoperative tumor detection in laparoscopic surgery. Our scenario is that the surgeon manipulates a sensor probe, makes a decision based on the feedback provided from the sensor, while simultaneously, the algorithm analyzes the time series of the sensor output. Thus, the algorithm assists the surgeon in making decisions by providing independent detection results. A deep neural network model with three hidden layers was used to analyze the sensor output. We propose methods to input the time series of the sensor output to the model for real-time analysis, and to determine the criterion for detection by the model. This study aims to validate the feasibility of the algorithm by using data acquired in our previous psychophysical experiment. There, novice participants were asked to detect a phantom of an early-stage gastric tumor through visual feedback from the tactile sensor. In addition to the analysis of the accuracy, signal detection theory was employed to assess the potential detection performance of the model. The detection performance was compared with that of human participants. We conducted two types of validation, and found that the detection performance of the model was not significantly different from that of the human participants if the data from a known user was included in the model construction. The result supports the feasibility of the proposed algorithm for detection assistance in computer-aided palpation.

SUBMITTER: Fukuda T

PROVIDER: S-EPMC7806085 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation.

Fukuda Tomohiro T Tanaka Yoshihiro Y Fujiwara Michitaka M Sano Akihito A

Frontiers in robotics and AI 20180619

Tactile sensory input of surgeons is severely limited in minimally invasive surgery, therefore manual palpation cannot be performed for intraoperative tumor detection. Computer-aided palpation, in which tactile information is acquired by devices and relayed to the surgeon, is one solution for overcoming this limitation. An important design factor is the method by which the acquired information is fed back to the surgeon. However, currently there is no systematic method for achieving this aim, an ...[more]

PMID: 33500950

Similar Datasets

Project description:BackgroundAlthough miniscrews are widely used in orthodontic treatment as temporary anchorage devices, their correct and safe placement has attracted little attention. This study aimed to introduce a novel cone beam CT (CBCT) image-based computer aided design and computer aided manufacturing (CAD-CAM) template for orthodontic miniscrew implantation and to evaluate the effectiveness of miniscrews implanted under the guidance of this template.MethodsThe CBCT scans of ten patients requiring miniscrews as anchorage were analyzed in NNT software to predetermine the insertion sites of miniscrew implants. The DICOM data of the scans, along with virtual miniscrews acquired in Solidworks software, were imported into Mimics software to construct three-dimensional (3D) images of teeth and bone and to determine the virtual position of miniscrews and 3D virtual templates were designed following consideration of the virtual implantation plans. A STL (Stereolithography) file of the virtual template was output, and the resin template was then fabricated with a stereolithographic appliance (SLA). 24 Miniscrews were then implanted guided by the template and clinical evaluation of their safety and stability, as well as their placement deviations, were made. A dental casts model and cephalometric analysis before and after orthodontic treatment were made to assess the dentomaxillofacial changes.ResultsAll 24 miniscrews had no contact with adjacent roots. 18 miniscrews had a grade I safety score and six had a grade II. The miniscrews were stable at 1, 3, 6, and 9 months after implantation, although there was mild inflammation around two miniscrews. Implantation deviation of miniscrew in the crown was (1.03±0.65) and (1.26±0.72) mm in the apex, on average. Satisfactory dentomaxillofacial changes in 10 patients with these 24 miniscrews as anchorage were acquired.ConclusionsMiniscrews could be implanted in the targeted position safely and precisely when guided by the novel templates, and remained stable during orthodontic treatment. Patients treated with these miniscrews as anchorage in orthodontic treatment acquired satisfactory dentomaxillofacial changes.

Dataset Information

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation.

Publications

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets