IMAGE PROCESSING DEVICE AND IMAGE PROCESSING METHOD IN IMAGE PROCESSING DEVICE

• US 20110255759A1
• Filed: 06/24/2011
• Published: 10/20/2011
• Est. Priority Date: 12/28/2005
• Status: Active Grant

• Current Assignee: Olympus Corporation
• Original Assignee: Olympus Medical Systems Corporation (Olympus Corporation)
• Inventors: NONAMI, Tetsuo, NISHIMURA, Hirokazu
• Granted Patent: US 8,300,955 B2
• Time in Patent Office: Days
• US Class Current: 382/128
• CPC Class Codes: A61B 1/00016 using wireless means
• CPC Class Codes: A61B 1/00036 Means for power saving, e.g. sleeping mode
• CPC Class Codes: A61B 1/00055 for alerting the user
• CPC Class Codes: A61B 1/041 Capsule endoscopes for imaging
• CPC Class Codes: A61B 5/073 Intestinal transmitters
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10068 Endoscopic image
• CPC Class Codes: G06T 2207/30028 Colon; Small intestine
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

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.

Claims

1. An image processing device comprising:

an image signal input portion for inputting an image signal on the basis of images obtained by medical equipment having an imaging function;

an image dividing portion for dividing the plurality of images into a plurality of regions, respectively, on the basis of the image signal inputted in the image signal input portion;

a feature value calculation portion for calculating a plurality of types of feature values in each of the plurality of regions divided by the image dividing portion;

a first cluster classifying portion for generating a plurality of clusters in one feature space on the basis of one type of feature value and the occurrence frequency of the one type of feature value in the plurality of types of feature values and for classifying the plurality of clusters into any one of a plurality of classes, respectively;

a second cluster classifying portion for generating a plurality of clusters in another feature space on the basis of another type of feature value and the occurrence frequency of the another type of feature value in the plurality of types of feature values and for classifying the plurality of clusters into any one of the plurality of classes, respectively; and

a cluster division portion for carrying out division processing for the plurality of clusters in the one feature space on the basis of a distribution state of the feature value in the one feature space and the another feature space.

2. An image processing method in an image processing device comprising:

an image dividing step for dividing an image into a plurality of regions, respectively, on the basis of an image signal inputted on the basis of the image obtained by medical equipment having an imaging function;

a feature value calculation step for calculating a plurality of types of feature values in each of the plurality of regions divided by the image dividing step;

a first cluster classifying step for generating a plurality of clusters in one feature space on the basis of one type of feature value and the occurrence frequency of the one type of feature value in the plurality of types of feature values and for classifying the plurality of clusters into any one of a plurality of classes, respectively;

a second cluster classifying step for generating a plurality of clusters in another feature space on the basis of another type of feature value and the occurrence frequency of the another type of feature value in the plurality of types of feature values and for classifying the plurality of clusters into any one of the plurality of classes, respectively; and

a cluster division step for carrying out division processing for the plurality of clusters in the one feature space on the basis of a distribution state of the feature value in the one feature space and the another feature space.

3. An image processing method in an image processing device comprising:

dividing an image obtained by medical equipment into a plurality of regions;

calculating one or more feature values in each of the plurality of regions;

generating a plurality of clusters in one feature space on the basis of one type of feature value and the occurrence frequency of the one type of feature value in the plurality of types of feature values and classifying the plurality of clusters into any one of a plurality of classes, respectively;

generating a plurality of clusters in another feature space on the basis of another type of feature value and the occurrence frequency of the another type of feature value in the plurality of types of feature values and classifying the plurality of clusters into any one of the plurality of classes, respectively; and

carrying out division processing for the plurality of clusters generated in the one feature space on the basis of a distribution state of the feature value in the one feature space and the another feature space.