# US 12,002,271 B2 · Identification device, scanner system, and identification method

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- Number: US 12,002,271 B2
- Document ID: US12002271B2
- Status: Granted
- Kind: B2
- Application number: 17/415,263
- Filed: 2019-12-12
- Published: 2022-02-24
- Granted: 2024-06-04
- Earliest claimed: 2018-12-17
- Assignees: J. Morita Mfg. Corp.
- Applicants: J. Morita Mfg. Corp.
- Inventors: Manabu Hashimoto; Ryosuke Kaji; Mikinori Nishimura
- Web page: https://patentgrep.com/patent/US12002271B2

## CPC

- A61C 9/0053: {Optical means or methods, e.g. scanning the teeth by a laser or light beam}
- G06V 20/64: Three-dimensional [3D] objects
- A61B 1/24: for the mouth, i.e. stomatoscopes, e.g. with tongue depressors; Instruments for opening or keeping open the mouth
- A61B 5/0062: {Arrangements for scanning}
- A61B 5/0088: {for oral or dental tissue}
- A61B 5/4547: {Evaluating teeth}
- A61C 19/04: Measuring instruments specially adapted for dentistry ({A61C5/44 takes precedence; testing vitality of teeth A61B5/0534;} radiation diagnosis specially adapted for dentistry A61B6/51)
- G06F 18/214: Generating training patterns; Bootstrap methods, e.g. bagging or boosting
- G06V 10/40: Extraction of image or video features
- G06V 10/56: relating to colour
- G06V 10/774: Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
- G06V 10/82: using neural networks
- G16H 30/40: for processing medical images, e.g. editing
- G16H 50/50: for simulation or modelling of medical disorders
- G06V 2201/03: Recognition of patterns in medical or anatomical images
- A61C: DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE (non-driven toothbrushes A46B; {tongue scrapers A61B17/24;} preparations for dentistry A61K6/00; preparations for cleaning the teeth or mouth A61K8/00, A61Q11/00)
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

An identification device includes: an input unit that receives three-dimensional data including data of a tooth; an identification unit that identifies a type of the tooth based on the three-dimensional data including a feature of the tooth received by the input unit and an estimation model including a neural network; and an output unit that outputs an identification result obtained by the identification unit.

## Claims

### Claim 1

An identification device that identifies a type of a tooth, the identification device comprising:
an input unit that receives three-dimensional data including data of the tooth;
an identification unit that identifies a type of the tooth based on
the three-dimensional data including a feature of the tooth received by the input unit, and
an estimation model including a neural network; and
an output unit that outputs an identification result obtained by the identification unit,
wherein
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in an upper jaw, a three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on an upper lip side; an image of an area on a palate side; and an image of an area on an incisal edge side,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the upper jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a buccal side, an image of an area on a palate side, and an image of an occlusion area,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in a lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a lower lip side, an image of an area on a tongue side, and an image of an area on the incisal edge side, and
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on the buccal side; an image of an area on the tongue side; and an image of the occlusion area.

### Claim 2 (depends on 1)

The identification device according to claim 1, wherein the estimation model is learned based on
tooth information corresponding to a type of the tooth associated with the three-dimensional data, and
the identification result including the type of the tooth that is obtained using the three-dimensional data.

### Claim 3 (depends on 1)

The identification device according to claim 1, wherein
the input unit receives at least the three-dimensional data corresponding to a plurality of teeth adjacent to the tooth and gums in an oral cavity, and
the identification unit identifies a type of each of the teeth based on the three-dimensional data including a feature of each of the teeth.

### Claim 4 (depends on 1)

The identification device according to claim 1, wherein the three-dimensional data includes three-dimensional position information at each of a plurality of points forming the tooth corresponding to the three-dimensional data.

### Claim 5 (depends on 4)

The identification device according to claim 4, wherein the position information includes coordinates of an absolute position based on a predetermined position.

### Claim 6 (depends on 1)

The identification device according to claim 1, wherein a type of the tooth is identified further based on a normal line generated for each of a plurality of points forming the tooth corresponding to the three-dimensional data.

### Claim 7 (depends on 1)

The identification device according to claim 1, wherein
the output unit outputs the identification result to a display unit, and
the display unit shows at least one of an image, a character, a numeral, an icon, and a symbol that correspond to the identification result.

### Claim 8 (depends on 1)

The identification device according to claim 1, wherein
the output unit outputs the identification result to an audio output unit, and
the audio output unit outputs a sound corresponding to the identification result.

### Claim 9 (depends on 1)

The identification device according to claim 1, wherein
the output unit outputs the identification result to a server device, and
the server device stores an accumulation of the identification result.

### Claim 10 (depends on 2)

The identification device according to claim 2, wherein
the estimation model includes at least one of a weighting factor and a determination value as a parameter used by the neural network, and
the estimation model is learned by updating the parameter based on the tooth information and the identification result.

### Claim 11 (depends on 2)

The identification device according to claim 2, wherein the tooth information includes at least one piece of information of a color, a character, a numeral, and a symbol that are associated with a type of the tooth corresponding to the three-dimensional data.

### Claim 12 (depends on 2)

The identification device according to claim 2, wherein the tooth information is associated with the three-dimensional data to allow a range of each of a plurality of the teeth corresponding to the three-dimensional data to be specified.

### Claim 13 (depends on 2)

The identification device according to claim 2, wherein the tooth information is associated with each of a plurality of points forming the tooth corresponding to the three-dimensional data.

### Claim 14 (depends on 2)

The identification device according to claim 2, wherein the estimation model is learned based on attribute information related to a subject having the teeth, in addition to the tooth information and the identification result.

### Claim 15 (depends on 14)

The identification device according to claim 14, wherein the attribute information includes at least one piece of information of an age, a gender, a race, a height, a weight, and a place of residence about the subject.

### Claim 16

A scanner system that acquires shape information about a tooth, the scanner system comprising:
a three-dimensional scanner that acquires three-dimensional data including data of the tooth using a three-dimensional camera; and
an identification device that identifies a type of the tooth based on the three-dimensional data including a feature of the tooth acquired by the three-dimensional scanner, wherein
the identification device includes
an input unit that receives the three-dimensional data,
an identification unit that identifies a type of the tooth based on
the three-dimensional data including a feature of the tooth received by the input unit, and
an estimation model including a neural network, and
an output unit that outputs an identification result obtained by the identification unit,
wherein
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in an upper jaw, a three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on an upper lip side; an image of an area on a palate side; and an image of an area on an incisal edge side,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the upper jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a buccal side, an image of an area on a palate side, and an image of an occlusion area,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in a lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a lower lip side, an image of an area on a tongue side, and an image of an area on the incisal edge side, and
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on the buccal side; an image of an area on the tongue side; and an image of the occlusion area.

### Claim 17

An identification method of identifying a type of a tooth, the identification method comprising:
receiving three-dimensional data including data of the tooth;
identifying a type of the tooth based on
the three-dimensional data including a feature of the tooth, and
an estimation model including a neural network; and
outputting an identification result obtained by the identifying a type of the tooth,
wherein
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in an upper jaw, a three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on an upper lip side; an image of an area on a palate side; and an image of an area on an incisal edge side,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the upper jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a buccal side, an image of an area on a palate side, and an image of an occlusion area,
in a case where the tooth corresponding to the three-dimensional data received by the input unit is an incisor in a lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on a lower lip side, an image of an area on a tongue side, and an image of an area on the incisal edge side, and
in a case where the tooth corresponding to the three-dimensional data received by the input unit is each of a canine and a molar in the lower jaw, the three-dimensional image corresponding to the three-dimensional data includes at least: an image of an area on the buccal side; an image of an area on the tongue side; and an image of the occlusion area.