# US 2014/0193060 A1 · Reconstruction method of biological tissue image, apparatus therefor, and image display apparatus using the biological tissue image

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2014/0193060 A1
- Document ID: US20140193060A1
- Status: Published application
- Kind: A1
- Application number: 14/147,985
- Filed: 2014-01-06
- Published: 2014-07-10
- Earliest claimed: 2013-01-08
- Assignees: Canon Kabushiki Kaisha
- Applicants: Canon Kabushiki Kaisha
- Inventors: Koichi Tanji
- Web page: https://patentgrep.com/patent/US20140193060A1

## CPC

- G06T 7/0014: {using an image reference approach}
- G06T 7/11: Region-based segmentation
- G06T 12/00: Tomographic reconstruction from projections
- G06V 20/698: {Matching; Classification}
- G06T 2207/10056: Microscopic image
- G06T 2207/20021: Dividing image into blocks, subimages or windows
- G06T 2207/20081: Training; Learning
- G06T 2207/30024: Cell structures in vitro; Tissue sections in vitro
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING

## Abstract

The present invention provides a method for classifying biological tissues with high precision compared to a conventional method. When measuring a spectrum which has a two-dimensional distribution that is correlated with a slice of a biological tissue, and acquiring a biological tissue image from the two-dimensional measured spectrum, the method includes dividing an image region into a plurality of small blocks, and then reconstructing the biological tissue image by using the measured spectrum and a classifier corresponding to each of the regions.

## Claims

### Claim 1

A reconstruction method of a biological tissue image using a signal processing apparatus based on a measured spectrum correlated with a substance distributed within a biological tissue comprising:
acquiring, within an image region, the measured spectrum at each of plural points within the biological tissue;
dividing the image region into a plurality of small blocks;
selecting one or more of peaks of the measured spectrum in each of the small blocks;
acquiring a classifier corresponding to each of the small blocks; and
acquiring the biological tissue image per each of the small blocks based on the selected one or more of peaks and the corresponding classifier.

### Claim 2 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein the classifier to be applied to an image region is generated from classification conditions acquired per each of a plurality of small blocks, by a regression analysis of the classification conditions, and then the biological tissue image in the image region is generated by applying the classifier to the measured spectrum.

### Claim 3 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein the biological tissue images acquired per each of a plurality of small blocks are integrated to generate the biological tissue image in the image region.

### Claim 4 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein the classifier is generated by applying a training data to the measured spectrum.

### Claim 5 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein, at the selecting one or more of peaks of the measured spectrum, the peak for use in the classification is determined based on Mahalanobis distance defined by a ratio of an inter-group dispersion to an intra-group dispersion.

### Claim 6 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein, the measured spectrum is any of a spectrum in an ultraviolet region, a visible region and an infrared region, a Raman spectroscopic spectrum, and a mass spectrum.

### Claim 7 (depends on 1)

The reconstruction method of the biological tissue image according to claim 1, wherein, the biological tissue is a pathological tissue.

### Claim 8 (depends on 1)

A biological tissue image acquiring apparatus, wherein a biological tissue image is reconstructed by the method according to claim 1.

### Claim 9 (depends on 7)

An image display apparatus, wherein, at a pathological diagnosis, a lesion is displayed by the biological tissue image acquiring apparatus according to claim 7.

### Claim 10

A reconstruction method of a biological tissue image using a signal processing apparatus based on a measured spectrum correlated with a substance distributed within a biological tissue comprising:
acquiring the measured spectrum within the biological tissue;
acquiring morphological information from distribution information of a peak component in the measured spectrum;
acquiring a classifier; and
applying the classifier to both of the measured spectrum of the biological tissue and of the morphological information acquired from the distribution information of the peak component in the measured spectrum, to acquire the biological tissue image.

### Claim 11 (depends on 10)

The reconstruction method of the biological tissue image according to claim 10, wherein when the classifier is generated and the biological tissue image is reconstructed, both of the measured spectrum and a higher-order local autocorrelation which is acquired from distribution information thereof are used.