Biomedical subjects

Takayuki Kitasaka

Publications and source records attributed to Takayuki Kitasaka.

4 recordsLinked to original sources

PubMed2006

A method for bronchoscope tracking by combining a position sensor and image registration.

This paper describes a method for tracking a bronchoscope by combining a position sensor and image registration. A bronchoscopy guidance system is a tool for providing real-time navigation information acquired from pre-operative CT images to a physician during a bronchoscopic examination. In this system, one of the fundamental functions is tracking a bronchoscope's camera motion. Recently, a very small electromagnetic position sensor has become available. It is possible to insert this sensor into a bronchoscope's working channel to obtain the bronchoscope's camera motion. However, the accuracy of its output is inadequate for bronchoscope tracking. The proposed combination of the sensor and image registration between real and virtual bronchoscopic images derived from CT images is quite useful for improving tracking accuracy. Furthermore, this combination has enabled us to achieve a real-time bronchoscope guidance system. We performed evaluation experiments for the proposed method using a rubber phantom model. The experimental results showed that the proposed system allowed the bronchoscope's camera motion to be tracked at 2.5 frames per second.

Artificial Intelligence↗

PubMed2005

Development of a navigation-based CAD system for colon.

We propose a navigation-based computer aided diagnosis (CAD) system for the colon. When diagnosing the colon using virtual colonoscopy (VC), a physician makes a diagnosis by navigating (flying-through) the colon. However, the viewpoints and the viewing directions must be changed many times because the colon is a very long and winding organ with many folds. This is a time-consuming task for physicians. We propose a new navigation-based CAD system for the colon providing virtual unfolded (VU) views, which enables physicians to observe a large area of the colonic wall at a glance. This system generates VU, VC, and CT slice views that are perfectly synchronized. Polyp candidates, which are detected automatically, are overlaid on them. We applied the system to abdominal CT images. The experimental results showed that the system effectively generates VU views for observing colon regions.

Algorithms↗

PubMed2005

Automated nomenclature of bronchial branches extracted from CT images and its application to biopsy path planning in virtual bronchoscopy.

We propose a novel anatomical labeling algorithm for bronchial branches extracted from CT images. This method utilizes multiple branching models for anatomical labeling. In the actual labeling process, the method selects the best candidate models at each branching point. Also a special labeling procedure is proposed for the right upper lobe. As an application of the automated nomenclature of bronchial branches, we utilized anatomical labeling results for assisting biopsy planning. When a user inputs a target point around suspicious regions on the display of a virtual bronchoscopy (VB) system, the path to the desired position is displayed as a sequence of anatomical names of branches. We applied the proposed method to 25 cases of CT images. The labeling accuracy was about 90%. Also the paths to desired positions were generated by using anatomical names in VB.

Algorithms↗

PubMed2005

Hybrid bronchoscope tracking using a magnetic tracking sensor and image registration.

In this paper, we propose a hybrid method for tracking a bronchoscope that uses a combination of magnetic sensor tracking and image registration. The position of a magnetic sensor placed in the working channel of the bronchoscope is provided by a magnetic tracking system. Because of respiratory motion, the magnetic sensor provides only the approximate position and orientation of the bronchoscope in the coordinate system of a CT image acquired before the examination. The sensor position and orientation is used as the starting point for an intensity-based registration between real bronchoscopic video images and virtual bronchoscopic images generated from the CT image. The output transformation of the image registration process is the position and orientation of the bronchoscope in the CT image. We tested the proposed method using a bronchial phantom model. Virtual breathing motion was generated to simulate respiratory motion. The proposed hybrid method successfully tracked the bronchoscope at a rate of approximately 1 Hz.

Algorithms↗