IMAGE PROCESSING APPARATUS AND X-RAY DIAGNOSIS APPARATUS

• US 20150248757A1
• Filed: 03/02/2015
• Published: 09/03/2015
• Est. Priority Date: 02/28/2014
• Status: Active Grant

• Current Assignee: Canon Medical Systems Corporation (Canon Inc.)
• Original Assignee: Toshiba Medical Systems Corporation (Canon Inc.), Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: OHISHI, Satoru
• Granted Patent: US 10,453,184 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/10116 X-ray image
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 2207/20182 Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/11 Region-based segmentation

Abstract

An image processing apparatus includes an identification unit, a calculator, and an image processor. The identification unit identifies a group of pixels indicating an object of interest in medical image data. The calculator specifies a cross-section corresponding to the running direction of the object of interest indicated by the group of pixels in the medical image data. The image processor performs noise reduction on the cross-section identified.

Claims

1. An image processing apparatus, comprising:

an identification unit configured to identify a group of pixels indicating an object of interest in medical image data;

a calculator configured to specify a cross-section corresponding to a running direction of the object of interest based on the group of pixels in the medical image data; and

an image processor configured to perform noise reduction on the cross-section specified.

2. The image processing apparatus of claim 1, wherein the identification unit is configured to identify a portion corresponding to a blood vessel as the object of interest in the medical image data.

3. The image processing apparatus of claim 2, wherein the calculator is configured to compare the portion corresponding to the blood vessel with a predetermined diameter, specify a part of the portion having a diameter smaller than the predetermined diameter, and obtain a running direction of the part specified.

4. The image processing apparatus of claim 1, wherein

the identification unit is configured to

minimize the medical image data to remove a small diameter blood vessel from a blood vessel as the object of interest, and

obtain a difference between images before and after removal of the small diameter blood vessel to obtain the small diameter blood vessel.

5. The image processing apparatus of claim 1, wherein

the identification unit is configured to

specify blood vessels as the object of interest and obtain a diameter of each of the blood vessels, and

specify a blood vessel with a diameter equal to or smaller than a threshold from among the blood vessels.

6. The image processing apparatus of claim 2, wherein the calculator is configured to obtain a vector for each of predetermined segments of the blood vessel identified by the identification unit, and obtain a summation of vectors of the segments to specify the cross-section.

7. The image processing apparatus of claim 6, wherein the vector is a unit vector.

8. The image processing apparatus of claim 6, wherein the calculator is configured to obtain a diameter of the blood vessel based on the pixels indicating the blood vessel identified, and changes a length of the segments used for calculation of the vectors based on the diameter of the blood vessel.

9. The image processing apparatus of claim 1, wherein

the image processor is configured to

obtain a matching rate between a pixel value of a target pixel to which the noise reduction is applied and a pixel value of each of peripheral pixels around the target pixel, and determine a weight of each of the peripheral pixels according to the matching rate,

obtain a weighted average of the peripheral pixels based on the weight, and

obtain the pixel value of the target pixel based on the matching rate and the weighted average.

10. The image processing apparatus of claim 1, wherein

the medical image data is acquired based on a acquisition program for acquiring the medical image data, and

the calculator is configured to change the cross-section on which the noise reduction is to be performed according to the acquisition program.

11. An image processing apparatus, comprising:

an identification unit configured to identify a portion corresponding to a blood vessel as an object of interest in medical image data;

a calculator configured to calculate energy of each of three orthogonal cross-sections or area of the portion corresponding to the blood vessel projected on each of the three orthogonal cross-sections based on pixels identified; and

a processor configured to specify a cross-section to apply noise reduction to the medical image data based on the energy or the area.

12. An X-ray diagnosis apparatus, comprising:

a generation unit configured to generate medical image data;

an identification unit configured to identify a group of pixels indicating an object of interest in medical image data;

a calculator configured to specify a cross-section corresponding to a running direction of the object of interest based on the group of pixels in the medical image data; and

an image processor configured to perform noise reduction on the cross-section identified

13. An image processing apparatus, comprising:

an identification unit configured to identify a group of pixels indicating an object of interest in medical image data acquired continuously or intermittently at predetermined intervals;

a calculator configured to obtain a running direction of the object of interest based on the group of pixels in the medical image data based on medical image data to which noise reduction is to be applied and a set of medical image data acquired prior to the medical image data; and

an image processor configured to perform noise reduction according to the running direction.