CN106981090B - Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image - Google Patents
Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image Download PDFInfo
- Publication number
- CN106981090B CN106981090B CN201710084880.9A CN201710084880A CN106981090B CN 106981090 B CN106981090 B CN 106981090B CN 201710084880 A CN201710084880 A CN 201710084880A CN 106981090 B CN106981090 B CN 106981090B
- Authority
- CN
- China
- Prior art keywords
- image
- dimensional
- tomographic image
- position information
- pixel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
- Apparatus For Radiation Diagnosis (AREA)
Abstract
The invention discloses a three-dimensional reconstruction method for a stepping unidirectional beam scanning tomographic image in a tube, which comprises the steps of setting stepping linear speed of a stepping motor for the tomographic image scanned by a beam of a stepping single-mode fiber in the tube, determining the relative linear position of a pixel point in a one-dimensional space, performing polar coordinate transformation on a two-dimensional image pixel point of each image under the condition of determining the rotating speed of the stepping motor, determining the position of the pixel point in a two-dimensional plane, and integrating the plane position information to determine the static position of the pixel point in the relative three-dimensional space. According to the difference of the gray value of the reflection intensity of the light beam on each tomographic image, the distance difference between two adjacent images is calculated, and interpolation is performed by adopting a gray difference calculation mode, so that the characteristics of the three-dimensional image are more visualized. The invention can extract the image information in the tube, has high precision of reconstructing the image of the inner wall of the tube, and has good auxiliary effect on the judgment of the complex shape and the tissue characteristic of the inner wall of the cardiovascular for the diagnosis of the medical intervention operation.
Description
Technical Field
The invention relates to the technical field of three-dimensional reconstruction and visualization, in particular to a three-dimensional reconstruction method for a tomography image by in-tube stepping one-way beam scanning.
Background
In the field of medical image processing, there are many tomographic image extraction methods, and in particular, Magnetic Resonance Imaging (MRI) methods used in angiography used in coronary arteries and cardiovascular occlusion and bypass, and Computed Tomography (CT) methods used in detection have been widely used.
The three-dimensional reconstruction of the tomographic data is to restore the three-dimensional structure of the object to be detected from a series of two-dimensional tomographic images. The three-dimensional reconstruction and visualization are carried out on the medical tomography image, and more objective and vivid tissue and organ forms can be provided for the diagnosis of doctors, so that the characteristics of uncertainty and larger error possibly caused by depending on the subjective imagination and judgment of the doctors in the traditional diagnosis are overcome. Therefore, the three-dimensional tomographic image reconstruction technique has wide clinical applicability.
The prior published patent applications were retrieved as follows:
1. a method (CN101533518B) for reconstructing a three-dimensional target object surface from a non-parallel tomographic image sequence discloses a method for reconstructing a three-dimensional target object surface from a non-parallel tomographic image sequence, which extracts a target object contour by segmenting a tomographic image, and performs distance conversion on the extracted contour, extracting a disc set and removing redundancy to find a maximum disc set within the target object contour, selecting a disc set for interpolation in an adjacent tomographic image, calculating a vector value of each point in the tomographic image pointing to the target object in the image, determining a distance of spatial points between the interpolated tomographic images, and performing a contour-based surface rendering display, and has a drawback in that an interpolation manner for the disc set is not based on plane position information of the target object in a specific tomographic image but is three-dimensional contour information reconstructed by calculating a vector value of each point in the tomographic image pointing to the target object in the image, the authenticity of the target object cannot be ensured.
2. A three-dimensional reconstruction method and a system (CN104599316A) with adjustable fault direction of a cone beam for scanning and reconstructing an object disclose a three-dimensional reconstruction method and a system with adjustable fault direction of a cone beam, the method can reconstruct the image of the fault of the object to be measured in any direction, in addition, the method can only reconstruct the interested area, avoids the reconstruction of the area outside the interested area, thereby reducing the calculated amount and improving the reconstruction speed. Characterized in that the method comprises the following steps: (1) scanning the detected object through a CT system; (2) reconstructing the scanning data of the CT system through a pre-reconstruction module; (3) obtaining image coordinate system parameters corresponding to the view tomograms through parameter adjustment; (4) the method has the defects that only the interested region is reconstructed, although the program calculation amount is reduced, the real shape of the target object cannot be ensured only on the precision of the reconstructed region, and the position of the target object is possibly lost.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a three-dimensional reconstruction method of an in-tube stepping one-way beam scanning tomographic image, which is simple, can be used for displaying at multiple angles and better reducing the image, describes the corresponding plane position information and stepping position information of the reconstructed image in a more intuitive mode, greatly improves the spatial resolution of the reconstructed three-dimensional image, and can comprehensively display the complex shape of the inner wall of a tube of a measured object and hierarchically display the tissue material characteristics of abnormal substances in the tube.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides a three-dimensional reconstruction method of an in-tube stepping unidirectional beam scanning tomographic image, which comprises the following steps of:
step S1, reading N tomographic images, wherein each tomographic image has N pieces of unidirectional light beam information at different positions, performing polar coordinate transformation on the tomographic image, and increasing the pixel density of the tomographic image by using an interpolation method to obtain N pieces of plane position information of pixels transformed according to a polar coordinate transformation formula;
the plane position information (X, Y) of each pixel transformed according to the polar coordinate transformation formula is obtained as follows: placing each piece of unidirectional light beam information of each tomography image from 1 to N, determining the density rho of the inserted pixels by the gray value of M pixel points on each light beam, and reading the N-th read pixeliTransforming the plane position information (X, Y) of one pixel in the tomographic image according to a polar coordinate transformation formula to obtain the plane position information (X, Y) of each pixel under the 2N-2N background; wherein n is more than or equal to 1i≤n；
Step S2, increasing the contrast of each tomography image transformed in the step S1 to obtain a visual map for display;
s3, extracting the contour of the target object by adopting an edge detection algorithm for the visual map obtained in the step S2, and determining the center of the contour circle;
step S4, obtaining step position information Z of each tomography image arranged in the three-dimensional space and vertical to each tomography image plane after being transformed in step S1 according to the step time and the step length of the tomography image acquisition equipment;
and S5, constructing a data structure of the three-dimensional entity according to the plane position information (X, Y) of each pixel of each tomography image transformed in the step S1, the contrast in the step S2, the center of the contour circle obtained in the step S3, the step position information Z obtained in the step S4 and the storage format of the tomography images, and displaying the three-dimensional entity by image processing software.
As a further optimization scheme of the three-dimensional reconstruction method for the in-tube stepping unidirectional beam scanning tomographic image, in step S1, the following formula is adopted to obtain the plane position information (X, Y) of each pixel;
where ρ is the density of the inserted pixels, ρ is known, (x, y) is the plane position information of each pixel point of each tomographic image, round (×) is a rounding function, M is the number of pixel points on each light beam in step S1, and N is the number of light beams on each tomographic image.
As a further optimization scheme of the three-dimensional reconstruction method for the in-tube stepping unidirectional beam scanning tomographic image, in step S3, extraction of edge contour plane position information is realized by setting a pixel gray threshold.
As a further optimization scheme of the three-dimensional reconstruction method of the in-tube stepping unidirectional beam scanning tomography image, the nth step in the step S4iThe image is on
The stepping position information Z of the time in the three-dimensional space is:
wherein, L is the total length of the collected object to be measured, T is the total time of the collection, the stepping speed
n is the number of acquired tomographic images.
As a further optimization scheme of the three-dimensional reconstruction method for the in-tube stepping unidirectional beam scanning tomographic image, in step S5, the iso-surface gradient of the target object in the three-dimensional space of each tomographic image is used for performing gray level difference calculation, so as to display a more real shape of the target object in the three-dimensional space.
Compared with the prior art, the invention adopting the technical scheme has the following technical effects: the invention provides the three-dimensional reconstruction method for the stepping one-way beam scanning tomographic image in the tube, which has the advantages of simple method, multi-angle display, better image restoration, capability of describing the corresponding plane position information and the stepping position information of the reconstructed image in a more intuitive mode, greatly improving the spatial resolution of the reconstructed three-dimensional image, capability of displaying the complex shape of the inner wall of the tube of a measured object in an all-around manner and capability of displaying the tissue material characteristics of abnormal substances in the tube in a layered manner.
Drawings
FIG. 1 is a flow chart of three-dimensional solid modeling based on a single-direction beam trajectory correction scan image.
FIG. 2 is an image comparison before and after polar transformation; in step S1, the reference numeral (a) denotes a tomographic image that has not undergone polar coordinate transformation, and the reference numeral (b) denotes a tomographic image that has undergone polar coordinate transformation in step S1.
FIG. 3 is a comparison of image frequency distribution histograms before and after polar transformation; wherein, (a) is the image frequency distribution histogram of the graph (a) in fig. 1, and (b) is the image frequency distribution histogram of the graph (b) in fig. 1.
FIG. 4 is the effect of the change of gray scale interval of four kinds of image contrast on the image; the contrast increasing display effect graph is (a) shown by Fa-2 Fb-55, (b) shown by Fa-0.5 Fb-55 decreasing contrast, and (c) shown by Fa-1 Fb-55 linear translation increasing brightness, and (d) shown by Fa-1 Fb-255 reversed contrast.
FIG. 5 is a graph of the effect of four changes in image contrast on an image histogram; wherein, (a) is Fa-2 Fb-55 contrast histogram increase, (b) is Fa-0.5 Fb-55 contrast histogram decrease, (c) is Fa-1 Fb-55 histogram linear shift luminance histogram increase, and (d) is Fa-1 Fb-255 histogram inversion histogram increase.
FIG. 6 is a display effect of an original image in a three-dimensional data field; wherein, (a) is an unprocessed original three-dimensional front image, and (b) is an unprocessed side three-dimensional image.
FIG. 7 is a three-dimensional display of an image after correction using a one-way beam trajectory; wherein, (a) is the processed original three-dimensional front image, and (b) is the processed original three-dimensional side image.
Detailed Description
According to the above disclosure, a three-dimensional solid modeling method based on a single-direction beam trajectory correction scan image according to the present invention is described in detail with reference to the accompanying drawings.
Referring to fig. 1, the three-dimensional solid modeling method based on the unidirectional beam trajectory correction scan image according to the present invention includes the steps of: step S1 of reading N tomographic images, each of which has N pieces of unidirectional light beam information at different positions, performing polar coordinate transformation on the tomographic image, and increasing the pixel density of the tomographic image by using an interpolation method to obtain N pieces of pixel point plane position information transformed according to a polar coordinate transformation formula, such as the effect after polar coordinate transformation shown in fig. 2, (a) in fig. 2 is the tomographic image without polar coordinate transformation in step S1, (b) in fig. 2 is the tomographic image after polar coordinate transformation in step S1, and comparison of image histograms before and after polar coordinate transformation shown in fig. 3; fig. 3 (a) is the image frequency distribution histogram of fig. 1 (a), and fig. 3 (b) is the image frequency distribution histogram of fig. 1 (b); step S2, increasing the contrast of each tomography image, such as the effect before and after the contrast change shown in FIG. 4, and the histogram change characteristics shown in FIG. 5 before and after the change; fig. 4 (a) is a graph showing an effect of increasing contrast by Fa-2 Fb-55, fig. 4 (b) is a graph showing a effect of decreasing contrast by Fa-0.5 Fb-55, fig. 4 (c) is a graph showing an effect of linearly translating by Fa-1 Fb-55 and showing an effect of increasing luminance by d in fig. 5 (Fa-1 Fb-255). Fig. 5 (a) shows a histogram of increased contrast with Fa being 2 Fb-55, (b) shows a histogram of decreased contrast with Fa being 0.5 Fb-55, (c) shows a histogram of increased linear luminance with Fa being 1 Fb-55, and (d) shows a histogram of inverted contrast with Fa being 1 Fb-255; step S3, extracting the contour of the inner wall of the blood vessel by using edge detection, determining the center of the contour circle, setting a gray threshold of a pixel point, and realizing the extraction of the plane position information of the edge contour; step S4, obtaining step position information Z of each tomography image arranged in the three-dimensional space and vertical to each tomography image plane after being transformed in step S1 according to the step time and the step length of the tomography image acquisition equipment; step S5, for the plane position information (X, Y) of each pixel of each tomographic image transformed in step S1, the contrast in step S2, the center of the contour circle in step S3, the step position information Z obtained in step S4, and the image storage format, a data structure of the three-dimensional entity is constructed, and the three-dimensional entity is displayed by the image processing software, as shown in fig. 6 and 7. FIG. 6 is a display effect of an original image in a three-dimensional data field; in fig. 6, (a) is an unprocessed original three-dimensional front image, and (b) is an unprocessed side three-dimensional image. FIG. 7 is a three-dimensional display of an image after correction using a one-way beam trajectory; in fig. 7, (a) is a processed original three-dimensional front image, and (b) is a processed original three-dimensional side image.
The invention is based on the pixel characteristics of the image, stores the tomographic image scanned by the unidirectional light beam into the memory space in blocks, displays the tomographic image in a three-dimensional scene, has good effect no matter the display effect of the tomographic image or the loading speed of the tomographic image, is mainly applied to the image of the tomographic scanning in the tube, and is a practical medical diagnosis auxiliary method.
The reconstruction step S2 is to pre-process the original tomographic image based on the original tomographic image, so as to provide a good description for the step S4. Obtaining a tomographic image of M X N pixels, loading the gray value of the tomographic image into a two-dimensional coordinate system, placing information of each unidirectional light beam of each tomographic image from 1 to N, assuming that the gray value of M pixel points is on each light beam, assuming that the density of an inserted pixel is represented by rho, the parameter is known, assuming that the coordinate of each pixel point of the tomographic image to be solved after polar coordinate transformation is represented by (X, Y), and transforming each pixel point (X, Y) of each tomographic image as follows:
position information (X, Y) of each pixel point under a 2N-by-2N background is obtained, so that the pixel density of the tomography image is only related to the density rho of the inserted pixels, the value of rho is appropriately increased, a tomography image which is clearer than an original tomography image can be obtained, and the tomography image is not distorted.
In order to develop a driving apparatus with controllable angular velocity and stepping velocity, the coordinate Z is used to represent stepping position information in the three-dimensional space in step S4, and assuming that the total length of the corresponding object to be measured is L and the total time of the acquisition is T, the stepping velocity is obtained
Since the number of the acquired tomographic images is n, the nthiThe image is on
The axial coordinate corresponding to the moment is as follows:
the function f (x, y, z) represents the gradient of the iso-surface, perpendicularOn the iso-surface, the gradient direction of each pixel point is the normal direction of the iso-surface at that point. And obtaining the coordinate of the vertex of the triangular plate and the normal vector thereof by interpolation of the coordinate value, the gray value and the gradient value of the vertex of the cube. Common interpolation methods are linear interpolation and midpoint selection. Let p1And p2Is coordinate value of two vertexes of any edge of the cube, and the gray value is I1And I2Normal vectors are n respectively1And n2And if the isosurface threshold is T, calculating the intersection point p and the normal vector n thereof by using a linear interpolation method according to the following formula:
if the midpoint selection method is adopted, the intersection point p is taken as the midpoint of the side, namely:
the calculation using the midpoint selection method is simpler and causes an error less than 1/2 for the side length of the cube. At present, the resolution of medical images is higher and higher, and three-dimensional images reconstructed by using a midpoint selection method and linear interpolation have no obvious visual difference.
The unit normal vector at the vertex (i, j, k) of the cube may be represented by the point gradient g ═ gi,gj,gk) Is calculated to have a value of
While the gradient at vertex (i, j, k) can be calculated by the gray scale difference, i.e.:
the normal vector of the vertex of the triangular plate can be obtained by the normal vector of the vertex of the cube through the interpolation method, and is used for calculating a three-dimensional model in the follow-up process so as to obtain vivid surface display.
In the three-dimensional entity construction method based on the unidirectional beam trajectory correction scanned image according to the present invention, in step S5, after the two-dimensional tomographic image is sequentially read into the memory to form the data field, the basic steps of extracting the iso-surface are as follows: the method comprises the following steps that firstly, two adjacent layers of data are scanned in sequence, and cubes are constructed one by one; secondly, comparing the gray value of each vertex of the cube with a given isosurface threshold value, and calculating an index value; thirdly, calculating the gradient of each vertex of the cube through gray difference for the cube containing the isosurface; fourthly, searching a side index table according to the index value to obtain an intersecting side of the current cube having an intersection point with the isosurface; fifthly, calculating coordinates and normal vectors of an equivalent point (an intersection point of the intersected edge and the equivalent surface) by interpolation according to two vertexes of the intersected edge and normal vectors thereof; sixthly, searching a triangular plate index table according to the index, and determining a combination mode of equivalent points forming a triangular plate in the current cube; and seventhly, forming an isosurface by triangular plates in the cube.
The invention is based on the pixel characteristics of the tomographic image, stores the image scanned by the unidirectional light beam into the memory space in blocks, and shows the image in the three-dimensional scene, and has good effect no matter the display effect of the tomographic image or the loading speed of the tomographic image.
Claims (5)
1. A three-dimensional reconstruction method for in-tube stepping one-way beam scanning tomography images is characterized by comprising the following steps:
step S1, reading N tomographic images, wherein each tomographic image has N pieces of unidirectional light beam information at different positions, performing polar coordinate transformation on the tomographic image, and increasing the pixel density of the tomographic image by using an interpolation method to obtain N pieces of plane position information of pixels transformed according to a polar coordinate transformation formula;
the plane position information (X, Y) of each pixel after the polar coordinate transformation formula is obtained as follows: placing each piece of unidirectional light beam information of each tomography image from 1 to N, determining the density rho of the inserted pixels by the gray value of M pixel points on each light beam, and reading the N-th read pixeliTransforming the plane position information (X, Y) of one pixel in the tomographic image according to a polar coordinate transformation formula to obtain the plane position information (X, Y) of each pixel under the 2N-2N background; wherein n is more than or equal to 1i≤n；
Step S2, increasing the contrast of each tomography image transformed in the step S1 to obtain a visual map for display;
s3, extracting the contour of the target object by adopting an edge detection algorithm for the visual map obtained in the step S2, and determining the center of the contour circle;
step S4, obtaining step position information Z transformed in step S1 according to the step time and the step length of the tomography image acquisition equipment, wherein the step position information Z is vertical to each tomography image plane arranged in the three-dimensional space;
and S5, constructing a data structure of the three-dimensional entity according to the plane position information (X, Y) of each pixel of each tomography image transformed in the step S1, the contrast in the step S2, the center of the contour circle obtained in the step S3, the step position information Z obtained in the step S4 and the storage format of the tomography images, and displaying the three-dimensional entity by image processing software.
2. The method for three-dimensional reconstruction of in-tube stepping one-way beam scanning tomographic image according to claim 1, wherein in step S1, the following formula is used to obtain the planar position information (X, Y) of each pixel;
where ρ is the density of the inserted pixels, ρ is known, (x, y) is the plane position information of each pixel point of each tomographic image, round (×) is a rounding function, M is the number of pixel points on each light beam in step S1, and N is the number of light beams on each tomographic image.
3. The method for reconstructing the three-dimensional tomographic image by in-tube stepping single-direction beam scanning as claimed in claim 1, wherein in step S3, the extraction of the edge contour plane position information is realized by setting a gray threshold of a pixel point.
4. The method for three-dimensional reconstruction of in-tube stepping one-way beam scanning tomographic image as claimed in claim 1, wherein the nth step in step S4iThe image is on
The stepping position information Z of the time in the three-dimensional space is:
wherein, L is the total length of the collected object to be measured, T is the total time of the collection, the stepping speed
n is the number of acquired tomographic images.
5. The method for three-dimensional reconstruction of tomographic images by in-tube stepping single-direction beam scanning as claimed in claim 1, wherein in step S5, the iso-surface gradient of the target object in the three-dimensional space of each tomographic image is used to perform gray difference calculation, thereby displaying the more realistic shape of the target object in the three-dimensional space.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710084880.9A CN106981090B (en) | 2017-02-16 | 2017-02-16 | Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710084880.9A CN106981090B (en) | 2017-02-16 | 2017-02-16 | Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106981090A CN106981090A (en) | 2017-07-25 |
| CN106981090B true CN106981090B (en) | 2020-04-28 |
Family
ID=59338255
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710084880.9A Active CN106981090B (en) | 2017-02-16 | 2017-02-16 | Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106981090B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107621463B (en) * | 2017-10-16 | 2024-03-22 | 苏州微景医学科技有限公司 | Image reconstruction method and device and microscopic imaging device |
| CN107678153B (en) | 2017-10-16 | 2020-08-11 | 苏州微景医学科技有限公司 | Optical fiber bundle image processing method and device |
| CN109410325B (en) * | 2018-11-01 | 2021-04-20 | 中国矿业大学(北京) | Monocular image sequence-based pipeline inner wall three-dimensional reconstruction method |
| CN111358496A (en) * | 2020-03-05 | 2020-07-03 | 成都翼诚电子有限公司 | Measuring method of large-angle imaging B-ultrasonic machine for animal for automatically measuring backfat |
| CN111797557B (en) * | 2020-07-03 | 2023-06-27 | 西安交通大学 | Sand dust geometric feature extraction and three-dimensional reconstruction method based on image processing |
| CN114322847B (en) * | 2022-03-15 | 2022-05-31 | 北京精雕科技集团有限公司 | Vectorization method and device for measured data of unidirectional scanning sensor |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101533518A (en) * | 2009-04-21 | 2009-09-16 | 山东大学 | Method for re-establishing surface of three dimensional target object by unparallel dislocation image sequence |
| EP2279695A1 (en) * | 2009-07-31 | 2011-02-02 | Medison Co., Ltd. | Sensor coordinate calibration in an ultrasound system |
| CN104574507A (en) * | 2015-01-14 | 2015-04-29 | 清华大学 | Three-dimensional entity construction method based on multiple tomography images |
| CN105616036A (en) * | 2015-12-23 | 2016-06-01 | 南京航空航天大学 | Direct entity 3D printing method based on medical cross-sectional images |
| WO2016131062A1 (en) * | 2015-02-13 | 2016-08-18 | Purdue Research Foundation | Tomography system |
-
2017
- 2017-02-16 CN CN201710084880.9A patent/CN106981090B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101533518A (en) * | 2009-04-21 | 2009-09-16 | 山东大学 | Method for re-establishing surface of three dimensional target object by unparallel dislocation image sequence |
| EP2279695A1 (en) * | 2009-07-31 | 2011-02-02 | Medison Co., Ltd. | Sensor coordinate calibration in an ultrasound system |
| CN104574507A (en) * | 2015-01-14 | 2015-04-29 | 清华大学 | Three-dimensional entity construction method based on multiple tomography images |
| WO2016131062A1 (en) * | 2015-02-13 | 2016-08-18 | Purdue Research Foundation | Tomography system |
| CN105616036A (en) * | 2015-12-23 | 2016-06-01 | 南京航空航天大学 | Direct entity 3D printing method based on medical cross-sectional images |
Non-Patent Citations (2)
| Title |
|---|
| Development of a vertebral endplate 3-D reconstruction technique;T.N. Huynh 等;《IEEE Transactions on Medical Imaging 》;19971031;第16卷(第5期);第689-696页 * |
| 用于荧光分子断层成像的小动物躯干部分三维表面轮廓重建研究;姚俊杰 等;《中国生物医学工程学报》;20080630;第27卷(第3期);第360-365页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106981090A (en) | 2017-07-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106981090B (en) | Three-dimensional reconstruction method for in-tube stepping unidirectional beam scanning tomographic image | |
| US4835688A (en) | Three-dimensional image processing apparatus | |
| US9858716B2 (en) | Fast three-dimensional visualization of object volumes without image reconstruction by direct display of acquired sensor data | |
| US4989142A (en) | Three-dimensional images obtained from tomographic slices with gantry tilt | |
| CN1765321A (en) | Method for obtaining visualization plaque sediment from three dimensional image data of blood vessel structure | |
| WO2022105647A1 (en) | Method for establishing enhanced three-dimensional model of intracranial angiography | |
| US20140375631A1 (en) | Image generation apparatus, method, and medium with image generation program recorded thereon | |
| JPH0731739B2 (en) | Method and apparatus for extracting faces in a two-dimensional tomographic slice | |
| US20090079736A1 (en) | Information processing apparatus and program | |
| CN114241077B (en) | CT image resolution optimization method and device | |
| CN110211193A (en) | Three dimensional CT interlayer image interpolation reparation and super-resolution processing method and device | |
| CN102132322B (en) | Apparatus for determining modification of size of object | |
| CN113506308A (en) | Deep learning-based vertebra positioning and spine segmentation method in medical image | |
| Svoboda et al. | Generation of synthetic image datasets for time-lapse fluorescence microscopy | |
| CN111009032A (en) | Blood vessel three-dimensional reconstruction method based on improved epipolar line constraint matching | |
| EP2483865A1 (en) | Medical image analysis system for anatomical images subject to deformation and related methods | |
| WO2011041475A1 (en) | Medical image analysis system using n-way belief propagation for anatomical images subject to deformation and related methods | |
| CN101996415B (en) | Three-dimensional modeling method for eyeball | |
| JPH021082A (en) | Apparatus and method for generating definition of three-dimensional surface | |
| CN112562058B (en) | Method for quickly establishing intracranial vascular simulation three-dimensional model based on transfer learning | |
| CN106023094A (en) | Image-based bone tissue microstructure restoration system and restoration method thereof | |
| CN116051553B (en) | Method and device for marking inside three-dimensional medical model | |
| CN116758087A (en) | Lumbar vertebra CT bone window side recess gap detection method and device | |
| Grandhe et al. | Adaptive analysis & reconstruction of 3D DICOM images using enhancement based SBIR algorithm over MRI | |
| US20220164967A1 (en) | Method of establishing an enhanced three-dimensional model of intracranial angiography |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |