Abstract:
When an operation instruction is input by a first (second) control output instruction input device, locus calculation means calculates a locus of movement of a first (second) therapeutic device on the basis of any one of joint sections, which is instructed to operate. On the basis of a calculation result by the locus calculation means, therapeutic device operation control means controls an operation of the first (second) therapeutic device by a first (second) active mechanism. Thereby, there is provided an endoscope apparatus which can improve the operational efficiency and positional precision of the therapeutic device.
Abstract:
A medical device system includes a manipulator including a plurality of joints, a parameter storing portion for storing joint parameters, including a largest available force, of each joint of the plurality of joints, a trajectory inputting portion for inputting, as a trajectory plan, trajectories for moving a distal end of the manipulator from a current position and attitude to a target position and attitude, a trajectory setting portion for setting a joint angle trajectory for each joint providing a largest available force from among joint angle trajectories which allow movement to the target position and attitude with a minimum number of driven joints based on a largest available force parameter for the each joint stored in the parameter storing portion and the trajectory plan.
Abstract:
A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.
Abstract:
A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.
Abstract:
The position of an antenna incorporated in a capsule-type endoscope 3 that moves in a body is estimated using a plurality of antennae, and where the distance dij between two positions Pti and P(t−1)j estimated at adjacent times falls within a predetermined value, pieces of information for these positions are related to each other and stored in a memory as connection information. Subsequently, processing for searching for a route from the connection information stored in the memory and calculating a track is performed.
Abstract:
A plurality of images inputted in an image signal input portion are divided into a plurality of regions by an image dividing portion, and a feature value in each of the plurality of regions is calculated by a feature value calculation portion and divided into a plurality of subsets by a subset generation portion. On the other hand, a cluster classifying portion classifies a plurality of clusters generated in a feature space into any one of a plurality of classes on the basis of the feature value and occurrence frequency of the feature value. And a classification criterion calculation portion calculates a criterion of classification for classifying images included in one subset on the basis of a distribution state of the feature value in the feature space of each of the images included in the one subset.
Abstract:
A medical image processing apparatus includes a selection portion that selects a pixel of interest from an image composed of a plurality of pixels and obtained by picking up an image of a living tissue, a first feature value calculation portion that calculates a first feature value on the basis of color tone of the pixel of interest and color tones of surrounding pixels, a second feature value calculation portion that calculates a second feature value on the basis of the color tone of the pixel of interest and the color tones of surrounding pixels, an evaluation value calculation portion that calculates an evaluation value on the basis of the first feature value and the second feature value, and an evaluation value judgment portion that judges whether the pixel of interest is a pixel constituting the linear structure, on the basis of the evaluation value.
Abstract:
There is provided a medical image processing apparatus including an image-extracting section extracting a frame image from in vivo motion picture data picked up by an in vivo image pickup device or a plurality of consecutively picked-up still image data, and an image analysis section analyzing the frame image extracted by the image-extracting section to output an image analysis result. The image analysis section includes a first biological-feature detection section detecting a first biological feature, a second biological-feature detection section detecting, based on a detection result obtained by the first biological feature detection section, a second biological feature in a frame image picked up temporally before or after the image used for detection by the first biological feature detection section; and a condition determination section making a determination for a biological condition based on a detection result obtained by the second biological feature detection section to output the determination.