Multidetector computed-tomography (MDCT) scanners provide large high-resolution three-dimensional (3-D) images of the chest. MDCT scanning, when used in tandem with bronchoscopy, provides a state-of-the-art approach for lung-cancer assessment. We have been building and validating a lung-cancer assessment system, which enables virtual-bronchoscopic 3-D MDCT image analysis and follow-on image-guided bronchoscopy. A suitable path planning method is needed, however, for using this system. We describe a rapid, robust method for computing a set of 3-D airway-tree paths from MDCT images. The method first defines the skeleton of a given segmented 3-D chest image and then performs a multistage refinement of the skeleton to arrive at a final tree structure. The tree consists of a series of paths and branch structural data, suitable for quantitative airway analysis and smooth virtual navigation. A comparison of the method to a previously devised path-planning approach, using a set of human MDCT images, illustrates the efficacy of the method. Results are also presented for human lung-cancer assessment and the guidance of bronchoscopy.

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Three-dimensional path planning for virtual bronchoscopy

A method and system for identifying a portion of an image data is disclosed. The image data can include image data of an anatomy, such as a brain of a patient. The identified portion can be used for planning a procedure. The identified portions can include anatomical landmarks that can be used to determine anatomical targets of the patient. The plan can include a path or trajectory to reach the anatomical target.

Method for Planning a Surgical Procedure

A system and a method to determine an anatomical landmark in an anatomy, comprising: a processor operable to execute instructions; a memory system to store instructions to be executed by the processor and image data (45) of the anatomy; a display operable to display the determined anatomical landmark in the image data in the anatomy; and a user input to provide a seed datum (48) in the image data to the processor; wherein the processor is operable to execute instructions stored in the memory system to determine the anatomical landmark (52) in the anatomy based upon the seed datum in the image data.

System for identification of anatomical landmarks

A system including a processor and/or processor system can be used to create a plan for a procedure, such as a surgical procedure. The plan for the surgical procedure can be based on various elements, including determined anatomical landmarks that can be used to determine anatomical targets of a patient. The planning processor can be used to determine the anatomical landmarks and identify anatomical targets in image data of a subject, even if the anatomical targets are indistinguishable in the image data.

System for navigating a planned procedure within a body

Purpose
The optimal electrode trajectory is needed to assist surgeons in planning Deep Brain Stimulation (DBS). A method for image-based trajectory planning was developed and tested.

Automatic computation of electrode trajectories for Deep Brain Stimulation: a hybrid symbolic and numerical approach

This paper describes an improvement of automatic neurosurgical path searching algorithm which incorporates the structure of blood vessels. We have proposed an automatic searching method for surgical path planning on neurosurgery to realize minimally invasive operations within the range of soft tissues. This path searching is based on importance values we defined, and an anatomical structure database generated from MRI images and surgeon experiences. This paper introduces blood vessels into the path searching because we cannot give them damages during operation. We first obtain the structure of blood vessels from MRA, then also give them importance values, and finally incorporate the structure into path searching. Experimental results show that the path obtained by the proposed method is better than searching without vessel structure.

Neuropath planner–automatic path searching for neurosurgery

We are developing a neurosurgical planning system, and this paper presents a method of automatic path searching from skin surface of the head to tumor inside the brain The path obtained by our system is an optimal one in minimally invasive neurosurgery and it is calculated automatically based on a 3D atlas The 3D atlas is a voxel based 3D matrix, and consists of two parts, structural part and knowledge part The structural part includes the geometrical information with respect to each tissue The knowledge part is generated based on experiences of doctors, and numeric value is provided as importance value for each tissue The path searching consists of two steps, path finding and path smoothing Path finding is to select an optimal path from surface of the head to the affected part based on minimization of importance value integrating along with the path We applied the algorithm into a head MRI data set The path obtained by path finding is reformed smoothly to approach the natural path of surgeon

Automatic Path Searching for Minimally Invasive Neurosurgical Planning

New methods and software tools for automatic extraction of the ventricle system from magnetic resonance imagery (MRI) data, ventricle part classification, and realistic texturing are proposed to support Virtual Endoscopy (VE). Volume- and surface-based medical atlases are intensively used as templates in the methods. The processed ventricle-related surfaces are then utilized in a haptic-based system, which provides a surgeon with several basic functions simulating "virtual treatment" of hydrocephalus.

Realistic Virtual Endoscopy of the ventricle system and haptic-based surgical simulator of hydrocefalus treatment.

A new method for automatic ventricle part subdivision, classification and realistic texturing is proposed to simplify navigation for virtual endoscopy (VE). The method is based on finding distance transformations for input surfaces to fit a template surface. After surface co-registration, each point of the input surface is classified in accordance with the class of the nearest template point and then class-specific textures are applied.

A template-based method of ventricle part classification and realistic texturing for virtual ventriculoscopy

This paper describes a 3D image based collaboration system for telemedicine. This system enables doctor to observe 3D images transferred from image database through network, and also has collaboration function which operate 3D position of viewing of each doctor by 3D image displaying and data transferring through network. It is constructed based on server client style, and the server has the function of transferring data from a 3D image database and a collaboration record database, and also has control unit of transferring data between doctors during operating the system. The client has a user interface including operation part for parameter selection of viewing and sending comments, and display part for displaying 3D image based on volume rendering and 3D position and direction of observer by using avatar. Doctors can use this system to do collaboration work by sending comments with viewing 3D image each other. We implement this system in different platform including UNIX workstation and PC, and also supply Web browser based user interface for considering various user environments. We applied the 3D images of MRI in head for examining the structure of soft tissues and tumor in detail. We also evaluated the performance of the system through network including LAN and Internet, and experimental result shows that this system is useful.

Toshiaki Mito

Papers

Neuropath planner–automatic path searching for neurosurgery

Automatic Path Searching for Minimally Invasive Neurosurgical Planning

Realistic Virtual Endoscopy of the ventricle system and haptic-based surgical simulator of hydrocefalus treatment.

A template-based method of ventricle part classification and realistic texturing for virtual ventriculoscopy

3D-image-based collaboration system for telemedicine