Neurosurgical robot Minerva: First results and current developments

Glauser, D.; Fankhauser, Heinz; Epitaux, M.; Hefti, J.‐L.; Jaccottet, A.

doi:10.1002/(sici)1522-712x(1995)1:5<266::aid-igs2>3.0.co;2-8

Cited by 112 publications

(42 citation statements)

References 11 publications

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“…According to them the increased precision can dramatically improve certain new types of treatments. For instance, implantation of semipermeable capsules containing living cells, which can produce locally the lacking neurotransmitters, could be better fitted for robotic surgery than for manual operation (Glauser et al 1995) …”

Section: Surgical Robotsmentioning

confidence: 99%

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Algorithms for modeling anatomic and target volumes in image‐guided neurosurgery and radiotherapy

Alakuijala¹

2002

Medical Physics

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The use of image-guidance in surgery and radiotherapy has significantly improved patient outcome in neurosurgery and radiotherapy treatments. This work developed volume definition and verification techniques for image-guided applications, using a number of algorithms ranging from image processing to visualization.Stereoscopic visualization, volumetric tumor model overlaid on an ultrasound image, and visualization of the treatment geometry were experimented with on a neurosurgical workstation. Visualization and volume definition tools were developed for radiotherapy treatment planning system.The magnetic resonance inhomogeneity correction developed in this work, possibly the first published data-driven method with wide applicability, automatically mitigates the RF field inhomogeneity artefact present in magnetic resonance images. Correcting the RF inhomogeneity improves the accuracy of the generated volumetric models.Various techniques to improve region growing are also presented. The simplex search method and combinatory similarity terms were used to improve the similarity function with a low additional computational cost and high yield in region correctness. Moreover, the effects of different priority queue implementations were studied.A fast algorithm for calculating high-quality digitally reconstructed radiographs has been developed and shown to better meet typical radiotherapy needs than the two alternative algorithms. A novel visualization method, beam's light view, is presented. It uses texture mapping for projecting the fluence of a radiation field on an arbitrary surface.This work suggests several improved algorithms for image processing, segmentation, and visualization used in image-guided treatment systems. The presented algorithms increase the accuracy of image-guidance, which can further improve the applicability and efficiency of imageguided treatments.

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Section: Surgical Robotsmentioning

confidence: 99%

“…Another neurosurgical robotic research group (Glauser et al 1995) has used a similar optimization-based approach. They used an error-back-propagation neural net in combination with a conventional kinematic model and minimized the error between measurements and the kinematics by this additional mechanism.…”

mentioning

confidence: 99%

Algorithms for modeling anatomic and target volumes in image‐guided neurosurgery and radiotherapy

Alakuijala¹

2002

Medical Physics

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“…Several robotic systems have been purposely developed for CT-guided interventions. A system named Minerva was designed for stereotactic neurosurgery at the Micro-engineering Laboratory of the Swiss Federal Institute of Technology Center [3]. Masamune et al developed a minimally invasive surgical system for neurosurgery [6].…”

Section: Introductionmentioning

confidence: 99%

Robotic Assisted Radio-Frequency Ablation of Liver Tumors – Randomized Patient Study

Patriciu

Awad

Solomon

et al. 2005

Lecture Notes in Computer Science

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Abstract. The minimally invasive treatment of liver tumors represents an alternative to the open surgery approach. Radio-frequency ablation destroys a tumor by delivering radio-frequency energy through a needle probe. Traditionally, the probe is placed manually using imaging feedback. New approaches use robotic devices to accurately place the instrument at the target. The authors developed an image-guided robotic system for percutaneous interventions using computed tomography. The paper presents a randomized patient study comparing the manual versus robotic needle placement for radio-frequency ablation procedures of liver tumors. The results of this study show that in our case robotic interventions were a very viable solution. Several treatment parameters such as radiation exposures and procedure-times were found to be significantly improved in the robotic case.

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“…The target applications in these early trials in using a robot for stereotactic interventions with a CT scanner were stereotactic brain surgery in combination with a head frame [7][8] [9]. Glauser et al also used a stereotactic head frame to register the robot and image space, but are able to perform needle placement under active CT surveillance to confirm the position of their end effector [10]. Similarly, Masamune et al performed needle placement within the CT scanner and registered using a stereotactic head frame [11].…”

Section: Introductionmentioning

confidence: 99%

A New Robotic System for Visually Controlled Percutaneous Interventions under CT Fluoroscopy

Loser

Navab

2000

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000

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Abstract. Minimally invasive CT-guided interventions are an attractive option for diagnostic biopsy and localized therapy delivery. This paper describes the concept of a new prototypical robotic tool, developed in a preliminary study for radiological image-guided interventions. Its very compact and light design is optimized for usage inside a CT-gantry, where a bulky robot is inappropriate, especially together with a stout patient and long stiff instruments like biopsy needles or a trocar. Additionally, a new automatic image-guided control based on "visual servoing" is presented for automatic and uncalibrated needle placement under CT-fluoroscopy. Visual servoing is well established in the field of industrial robotics, when using CCD cameras. We adapted this approach and optimized it for CT-fluoroscopy-guided interventions. It is a simple and accurate method which requires no prior calibration or registration. Therefore, no additional sensors (infrared, laser, ultrasound, etc), no stereotactic frame and no additional calibration phantom is needed. Our technique provides accurate 3D alignment of the needle with respect to an anatomic target. A first evaluation of the robot using CT fluoroscopy showed an accuracy in needle placement of ±0.4 mm (principle accuracy) and ±1.6 mm in a small pig study. These first promising results present our method as a possible alternative to other needle placement techniques requiring cumbersome and time consuming calibration procedures.

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Neurosurgical robot Minerva: First results and current developments

Cited by 112 publications

References 11 publications

Algorithms for modeling anatomic and target volumes in image‐guided neurosurgery and radiotherapy

Algorithms for modeling anatomic and target volumes in image‐guided neurosurgery and radiotherapy

Robotic Assisted Radio-Frequency Ablation of Liver Tumors – Randomized Patient Study

A New Robotic System for Visually Controlled Percutaneous Interventions under CT Fluoroscopy

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