CN104574263A - Quick three-dimensional ultrasonic reconstruction and display method on basis of GPU (graphics processing unit) - Google Patents

Quick three-dimensional ultrasonic reconstruction and display method on basis of GPU (graphics processing unit) Download PDF

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CN104574263A
CN104574263A CN201510044341.3A CN201510044341A CN104574263A CN 104574263 A CN104574263 A CN 104574263A CN 201510044341 A CN201510044341 A CN 201510044341A CN 104574263 A CN104574263 A CN 104574263A
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叶华山
丁明跃
张锐麟
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Hubei University of Science and Technology
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Hubei University of Science and Technology
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Abstract

The invention relates to a quick three-dimensional ultrasonic reconstruction and display method on the basis of a GPU (graphics processing unit). The quick three-dimensional ultrasonic reconstruction and display method includes steps of (1), acquiring and inputting images; (2), preprocessing two-dimensional images; (3), dividing and extracting tissues and organs; (4), three-dimensionally modeling the surfaces of the tissues; (5), visualizing three-dimensional medical images. The step (4) includes (4a) carrying out direct volume rendering on the basis of the GPU. The quick three-dimensional ultrasonic reconstruction and display method has the advantages that different types of three-dimensional reconstruction operation are carried out in the GPU, and accordingly the image display speeds can be greatly increased.

Description

The ultrasonic reconstruction of a kind of quick three-dimensional based on GPU and display packing
Technical field
The present invention relates to 3-D supersonic imaging technical field, particularly the ultrasonic reconstruction of a kind of quick three-dimensional based on GPU and display packing.
Background technology
The application of current 3-D supersonic imaging in clinical is more and more extensive, become important medical diagnosis means, but the function and efficacy of 3-D supersonic imaging also not yet meets the requirement of clinical practice, also there is problems and development space in the speed of imaging, quality and accuracy.
The speed of current 3-D supersonic imaging has had huge leaping compared with in the past, but still need faster three-dimensional reconstruction speed to meet the requirement of clinical practice; And the resolution of 3-D view is not high, three-dimensional ultrasound pattern is applied and is restricted.In addition, current most three-dimension ultrasonic imaging systems can complete the accurate measurement of many medical parameters, but accurate not enough and perfect in volume, the isoparametric measurement of surface area.
Summary of the invention
The technical problem to be solved in the present invention is: in order to the function and efficacy overcoming existing 3-D supersonic imaging also not yet meets the requirement of clinical practice, the speed of imaging, quality and accuracy also exist the deficiency of problems and development space, the invention provides the ultrasonic reconstruction of a kind of quick three-dimensional based on GPU and display packing.
The technical solution adopted for the present invention to solve the technical problems is: the ultrasonic reconstruction of a kind of quick three-dimensional based on GPU and display packing, comprise the following steps:
(1) Image Acquisition and input:
(1a) the two-dimentional tomography sequence image generated by physical equipment, through medium or Internet Transmission to 3-D imaging system;
(1b) arrange reconstructing system in 3-D imaging system, reconstructing system reads described two-dimentional tomography sequence image, and described two-dimentional tomography sequence image, through format conversion, image normalization process, finally converts bitmap to;
(2) pre-service of two dimensional image:
(2a) filtering is carried out to the bitmap of step (1b);
(2b) image enhaucament: strengthen organ or organizational boundary;
(2c) registration of image and data fusion: the medical image of different modalities is organically combined and is reflected on piece image;
(2d) interpolation between faultage image: add virtual sliced sheet between sectioning image;
(3) segmentation of histoorgan and extraction:
(3a) auto Segmentation is organized;
(3b) Interactive Segmentation;
(3c) extraction of cut zone and record: the tissue that recording step (3b) is partitioned into or organ, with voxel form record;
(4) the three-dimensional surface modeling of tissue:
(4a) based on the direct volume drawing modeling of GPU;
(4b) model is lattice simplified;
(5) 3 d medical images is visual:
(5a) model color is arranged;
(5b) 3-D display of model: the 3-D display that tissue, organ or focus are provided;
(5c) geometric operation of model, so that user's tissues observed structure from different perspectives;
(5d) model cutting, window, extract operation: in given plane, cutting is carried out to reconstruction tissue, observes the relation of focus and surrounding tissue.
In step (4a), the direct volume drawing modeling based on GPU adopts based on 2D texture volume rendering algorithm, based on 3D texture volume rendering algorithm or the light projecting algorithm based on GPU.
When adopting based on 2D texture volume rendering algorithm, for each coordinate axis in three dimensions, define a pair layer stack and corresponding 2D texture storehouse respectively, require that the lamella in sheet layer stack is vertical with corresponding coordinate axis; When drawing, select to draw closest to vertical a pair layer stack and 2D texture storehouse with direction of observation.
When adopting based on 2D texture volume rendering algorithm, when drawing lamella, utilizing the bilinear interpolation function that 2D grain hardware carries, texture is sampled, thus realize sampling to the bilinear interpolation of volume data.
When adopting based on 3D texture volume rendering algorithm, any position that line of vision lamella can be arranged in three-dimensional data space is carried out, thus utilizes 3D grain hardware, carries out Tri linear interpolation sampling to any position in three-dimensional data space.
When adopting the light projecting algorithm based on GPU, the specific implementation step based on the light projecting algorithm of GPU comprises:
(1) read volume data scalar value, be loaded into texture memory with three-D grain form;
(2) read in background data, be loaded into texture memory with 2 d texture form;
(3) calculate pre-integration look-up table, be loaded into texture memory with 2 d texture form;
(4) utilize the convolution operation in fragment shader, the scalar value of current sampling point obtained according to texture sampling and the scalar value of its surrounding sample points calculate the Grad (G of this point x, G y, G z), and be normalized;
(5) calculate half-angle vector H according to direction of illumination vector L and observer sight line V, be used for calculating spectral range, the Phong model be simplified:
H = L + V | L + V | Formula (5.1);
(6) by surround lighting coefficient k a, scattered light coefficient k d, specular light coefficient k stinter is imported into as consistent variable;
(7) illumination calculation is carried out according to Plong illumination model:
I=k ai a+ k ai l(NL)+k si l(NH) nformula (5.2);
(8) from ray cast point, circulating sampling, carries out texture lookups according to adjacent sample values, maps out corresponding color value and opaque value, and time row accumulation.
The invention has the beneficial effects as follows, the present invention is placed on all kinds of computings of three-dimensional reconstruction in GPU and carries out, and greatly improves the speed of image display.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the present invention is further described.
Fig. 1 is the theory diagram of three dimentional reconstruction of the present invention and display system.
Fig. 2 is the schematic diagram of light projecting algorithm.
Embodiment
In conjunction with the accompanying drawings, the present invention is further detailed explanation.These accompanying drawings are the schematic diagram of simplification, only basic structure of the present invention are described in a schematic way, and therefore it only shows the formation relevant with the present invention.
As shown in Figure 1, the ultrasonic reconstruction of a kind of quick three-dimensional based on GPU of the present invention and display packing, comprise the following steps:
(1) Image Acquisition and input:
(1a) the two-dimentional tomography sequence image generated by physical equipment, through medium or Internet Transmission to 3-D imaging system;
(1b) arrange reconstructing system in 3-D imaging system, reconstructing system reads described two-dimentional tomography sequence image, and described two-dimentional tomography sequence image, through format conversion, image normalization process, finally converts the bitmap irrelevant with described physical equipment to;
(1c) user selects suitable window width, window position and window transform technology to show image as required under Windows system.
(2) pre-service of two dimensional image:
(2a) filtering is carried out to the bitmap of step (1b): the random perturbation of electronic equipment in filtering imaging process and transmitting procedure, stress release treatment and distortion;
(2b) image enhaucament: strengthen organ or organizational boundary; Due to the fuzzy characteristic of medical image, must take measures to strengthen organ or organizational boundary, for follow-up segmentation is ready.
(2c) registration of image and data fusion: the medical image of different modalities organically combined and is reflected on piece image, providing the information such as human dissection, physiology and pathology more intuitively, galore.
(2d) interpolation between faultage image: add virtual sliced sheet between sectioning image; For ensureing that the 3-D view rebuild does not distort, undistorted, need to add virtual sliced sheet between sectioning image, thus ensure the effect of three-dimensional visualization.
(3) segmentation of histoorgan and extraction:
(3a) organize auto Segmentation: utilize mathematical mor-phology gradient image generation technique and watershed algorithm thereof, pre-segmentation is carried out to image;
(3b) Interactive Segmentation: the accurate segmentation realizing tissue or organ with human-computer interaction technology;
(3c) extraction of cut zone and record: the tissue that recording step (3b) is partitioned into or organ, with voxel form record;
(4) the three-dimensional surface modeling of tissue:
(4a) based on the direct volume drawing modeling of GPU;
(4b) model is lattice simplified;
(5) 3 d medical images is visual:
(5a) model color is arranged: setting or change tissue color, adopt translucent effect display; Show or hide tissue;
(5b) 3-D display of model: the 3-D display that tissue, organ or focus are provided;
(5c) geometric operation of model, comprises the operations such as rotation, translation, convergent-divergent, to use tissues observed structure all from different perspectives;
(5d) model cutting, window, extract operation: in given plane, cutting is carried out to reconstruction tissue, observes the relation of focus and surrounding tissue.This generic operation also comprises the operation such as the physical measurement of focus, the display of arbitrary section.
In step (4a), the direct volume drawing modeling based on GPU adopts based on 2D texture volume rendering algorithm, based on 3D texture volume rendering algorithm or the light projecting algorithm based on GPU.
Based on 2D texture volume rendering algorithm with based on 3D texture volume rendering algorithm:
In the volume drawing based on 2D texture, act on behalf of solid be one group of thing to lamella, this pack layer collection is called sheet layer stack.The 2D texture set generated by each lamella volume data is called 2D texture storehouse.For a pair layer stack and 2D texture storehouse, the 2D texture in the lamella in sheet layer stack and 2D texture storehouse is one to one.For each lamella, with the 2D texture corresponding to this lamella, texture is carried out to lamella.When drawing lamella, utilizing the bilinear interpolation function that 2D grain hardware carries, texture is sampled, thus realize sampling to the bilinear interpolation of volume data.
Although a 2D texture storehouse just can store whole volume data, for volume drawing or inadequate.If only have a pair layer stack and 2D texture storehouse, when direction of observation rotates to parallel to lamella with thing, because sampling ray passes between lamella, now the image of poor quality will be obtained.Solution is for each coordinate axis in three dimensions, defines a pair layer stack and corresponding 2D texture storehouse respectively, requires that the lamella in sheet layer stack is vertical with corresponding coordinate axis.When drawing, select to draw sheet layer stack and 2D texture storehouse closest to vertical that with direction of observation.
In the volume drawing based on 3D texture, acting on behalf of solid is one group of line of vision lamella, and namely these lamellas are all vertical at direction of observation.The cube be made up of three-dimensional data border becomes volume data bounding box.These line of vision lamellas are cross sections that the plane cutting volume data bounding box of a series of direction of observation is formed, and these cross sections are some polygons, usually also referred to as lamella polygon.When carrying out volume drawing, generating a 3D texture by whole volume data, and determining the transformational relation of volume data volume coordinate and volume data 3D texture coordinate.According to this relation, each summit of lamella polygon and 3D texture coordinate can be determined, thus utilize the texture sampling function (Tri linear interpolation) of 3D grain hardware, calculate the volume data sampled value on each sampled point of lamella polygonal internal.
In the volume drawing based on 3D texture, any position that line of vision lamella can be arranged in three-dimensional data space is carried out, thus can utilize 3D grain hardware, carries out Tri linear interpolation sampling to any position in three-dimensional data space.Therefore, the picture quality that the method obtains is better than the image produced based on 2D texture volume drawing.Because line of vision lamella can be positioned at any position in volume data space, so the change of sampling rate can realize simply by the quantity changing line of vision lamella.Meanwhile, because line of vision lamella is vertical with direction of observation, so when parallel projection, sampling interval keeps constant.
Because the texture memory of PC graphic hardware is limited, for fairly large medical volume data, volume data must be divided into several body block.And when carrying out 3D texture, whole 3D texture must be loaded in texture memory.Like this when carrying out volume drawing, the volume data Bulk transport between the Rendering operations of GPU and system hosts to texture memory cannot walk abreast, and causes drawing efficiency degradation.Although can by reducing body block size, the 3D texture of body block is made to take less texture memory space to increase the parallel velocity of GPU Rendering operations and data transmission, but it is very difficult to reach desirable load balance, and add the computing that GPU calculates lamella and body block bounding box intersection point.
Due to when carrying out texture sampling, volume drawing based on 2D texture only carries out bilinear interpolation, and Tri linear interpolation can be carried out based on the object plotting method of 3D texture, therefore based on the object plotting method performance of 2D texture and versatility stronger, and be better than the image that produces based on 2D texture volume drawing based on the picture quality that the object plotting method of 3D texture obtains.
Light projecting algorithm based on GPU:
Light projecting algorithm take image space as the volume rendering algorithm of sequence, suppose that each data point in 3 d data field has a color value and opacity, adopt the mode of parallel projection, assuming that viewpoint at infinity, according to the position of current view point, a ray is sent also through 3 d data field to 3 d data field through a certain pixel on screen, in data fields, select several equidistant resample points along this ray again, do interpolation to obtain resample points color value and opacity value by adjacent volume data.Then, adopt from front to back or after order forward the color value of sampled points all on this ray and opacity value are synthesized, thus obtain color value that on screen, this pixel is final and opacity value.Light projecting algorithm principle as shown in Figure 2.
Specific implementation step based on the light projecting algorithm of GPU comprises:
(1) read volume data scalar value, be loaded into texture memory with three-D grain form;
(2) read in background data, be loaded into texture memory with 2 d texture form;
(3) calculate pre-integration look-up table, be loaded into texture memory with 2 d texture form;
(4) utilize the convolution operation in fragment shader, the scalar value of current sampling point obtained according to texture sampling and the scalar value of its surrounding sample points calculate the Grad (G of this point x, G y, G z), and be normalized;
(5) calculate half-angle vector H according to direction of illumination vector L and observer sight line V, be used for calculating spectral range, the Phong model be simplified:
H = L + V | L + V | Formula (5.1);
(6) by surround lighting coefficient k a, scattered light coefficient k d, specular light coefficient k stinter is imported into as consistent variable;
(7) illumination calculation is carried out according to Plong illumination model:
I=k ai a+ k ai l(NL)+k si l(NH) nformula (5.2);
(8) from ray cast point, circulating sampling, carries out texture lookups according to adjacent sample values, maps out corresponding color value and opaque value, and time row accumulation.
Three kinds, table 1 is based on the feature of the direct volume drawing algorithm of GPU
With above-mentioned according to desirable embodiment of the present invention for enlightenment, by above-mentioned description, relevant staff in the scope not departing from this invention technological thought, can carry out various change and amendment completely.The technical scope of this invention is not limited to the content on instructions, must determine its technical scope according to right.

Claims (6)

1., based on the ultrasonic reconstruction of quick three-dimensional and a display packing of GPU, it is characterized in that comprising the following steps:
(1) Image Acquisition and input:
(1a) the two-dimentional tomography sequence image generated by physical equipment, through medium or Internet Transmission to 3-D imaging system;
(1b) arrange reconstructing system in 3-D imaging system, reconstructing system reads described two-dimentional tomography sequence image, and described two-dimentional tomography sequence image, through format conversion, image normalization process, finally converts bitmap to;
(2) pre-service of two dimensional image:
(2a) filtering is carried out to the bitmap of step (1b);
(2b) image enhaucament: strengthen organ or organizational boundary;
(2c) registration of image and data fusion: the medical image of different modalities is organically combined and is reflected on piece image;
(2d) interpolation between faultage image: add virtual sliced sheet between sectioning image;
(3) segmentation of histoorgan and extraction:
(3a) auto Segmentation is organized;
(3b) Interactive Segmentation;
(3c) extraction of cut zone and record: the tissue that recording step (3b) is partitioned into or organ, with voxel form record;
(4) the three-dimensional surface modeling of tissue:
(4a) based on the direct volume drawing modeling of GPU;
(4b) model is lattice simplified;
(5) 3 d medical images is visual:
(5a) model color is arranged;
(5b) 3-D display of model: the 3-D display that tissue, organ or focus are provided;
(5c) geometric operation of model, so that user's tissues observed structure from different perspectives;
(5d) model cutting, window, extract operation: in given plane, cutting is carried out to reconstruction tissue, observes the relation of focus and surrounding tissue.
2. as claimed in claim 1 based on the ultrasonic reconstruction of quick three-dimensional and the display packing of GPU, it is characterized in that: in step (4a), the direct volume drawing modeling based on GPU adopts based on 2D texture volume rendering algorithm, based on 3D texture volume rendering algorithm or the light projecting algorithm based on GPU.
3. as claimed in claim 2 based on the ultrasonic reconstruction of quick three-dimensional and the display packing of GPU, it is characterized in that: when adopting based on 2D texture volume rendering algorithm, for each coordinate axis in three dimensions, define a pair layer stack and corresponding 2D texture storehouse respectively, require that the lamella in sheet layer stack is vertical with corresponding coordinate axis; When drawing, select to draw closest to vertical a pair layer stack and 2D texture storehouse with direction of observation.
4. as claimed in claim 2 based on the ultrasonic reconstruction of quick three-dimensional and the display packing of GPU, it is characterized in that: when adopting based on 2D texture volume rendering algorithm, when drawing lamella, utilize the bilinear interpolation function that 2D grain hardware carries, texture is sampled, thus realizes sampling to the bilinear interpolation of volume data.
5. as claimed in claim 2 based on the ultrasonic reconstruction of quick three-dimensional and the display packing of GPU, it is characterized in that: when adopting based on 3D texture volume rendering algorithm, any position that line of vision lamella can be arranged in three-dimensional data space is carried out, thus utilize 3D grain hardware, Tri linear interpolation sampling is carried out to any position in three-dimensional data space.
6., as claimed in claim 2 based on the ultrasonic reconstruction of quick three-dimensional and the display packing of GPU, it is characterized in that: when adopting the light projecting algorithm based on GPU, the specific implementation step based on the light projecting algorithm of GPU comprises:
(1) read volume data scalar value, be loaded into texture memory with three-D grain form;
(2) read in background data, be loaded into texture memory with 2 d texture form;
(3) calculate pre-integration look-up table, be loaded into texture memory with 2 d texture form;
(4) utilize the convolution operation in fragment shader, the scalar value of current sampling point obtained according to texture sampling and the scalar value of its surrounding sample points calculate the Grad (G of this point x, G y, G z), and be normalized;
(5) calculate half-angle vector H according to direction of illumination vector L and observer sight line V, be used for calculating spectral range, the Phong model be simplified:
H = L + V | L + V | Formula (5.1);
(6) by surround lighting coefficient k a, scattered light coefficient k d, specular light coefficient k stinter is imported into as consistent variable;
(7) illumination calculation is carried out according to Plong illumination model:
I=k ai a+ k ai l(NL)+k si l(NH) nformula (5.2);
(8) from ray cast point, circulating sampling, carries out texture lookups according to adjacent sample values, maps out corresponding color value and opaque value, and time row accumulation.
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Cited By (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104915992A (en) * 2015-06-15 2015-09-16 上海应用技术学院 A real-time shadow volume rendering method based on femur CT images
CN105496453A (en) * 2015-11-13 2016-04-20 武汉科技大学 Cattle ovarian follicle ultrasonic monitoring system and monitoring method for same
CN105534476A (en) * 2015-12-05 2016-05-04 新乡医学院第一附属医院 Early detection system for kidney diseases and injuries of department of pediatrics
CN106023300A (en) * 2016-05-09 2016-10-12 深圳市瑞恩宁电子技术有限公司 Body rendering method and system of semitransparent material
CN107274428A (en) * 2017-08-03 2017-10-20 汕头市超声仪器研究所有限公司 Multi-target three-dimensional ultrasonic image partition method based on emulation and measured data
CN107862733A (en) * 2017-11-02 2018-03-30 南京大学 Large scale scene real-time three-dimensional method for reconstructing and system based on sight more new algorithm
CN108010115A (en) * 2017-10-30 2018-05-08 中国科学院深圳先进技术研究院 Multiplanar reconstruction method, apparatus, equipment and storage medium for CBCT imagings
CN108053465A (en) * 2017-12-11 2018-05-18 深圳市图智能科技有限公司 A kind of image segmentation result post-processing approach based on volume drawing
CN108354626A (en) * 2018-03-31 2018-08-03 华南理工大学 A variety of MV high clearing systems fast medical ultrasonic image systems based on GPU
CN108597012A (en) * 2018-04-16 2018-09-28 北京工业大学 A kind of three-dimensional rebuilding method of the medical image based on CUDA
CN109064543A (en) * 2018-08-30 2018-12-21 十维度(厦门)网络科技有限公司 A kind of graphical textures load rendering method
CN109754869A (en) * 2017-11-08 2019-05-14 通用电气公司 The rendering method and system of the corresponding coloring descriptor of the ultrasound image of coloring
CN110827401A (en) * 2019-11-15 2020-02-21 张军 Scanning imaging system for interventional therapy
CN111466954A (en) * 2020-05-25 2020-07-31 武汉中旗生物医疗电子有限公司 Three-dimensional ultrasonic stereo dissection chart generation method and device
CN112750520A (en) * 2020-12-31 2021-05-04 四川桑瑞思环境技术工程有限公司 Information processing system
CN113781635A (en) * 2021-09-10 2021-12-10 云从科技集团股份有限公司 Medical image projection method, medical image projection apparatus, computer device, and storage medium
CN116805347A (en) * 2023-08-22 2023-09-26 中国电子科技集团公司第十五研究所 Volume texture coating interpolation method based on volume data six-boundary surface geometric configuration

Non-Patent Citations (7)

* Cited by examiner, † Cited by third party
Title
刘磊: "基于GPU的医学图像三维重建及可视化技术研究", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
卜祥磊: "基于GPU的医学图像三维可视化技术研究", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
明星: "基于GPU的医学图像三维重建算法及其应用", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
汪欣: "基于体绘制方法的医学图像三维重建研究", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
王昊: "基于GPU的肝脏三维可视化系统的设计与实现", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
王珊珊: "医学影像处理分析系统中的可视化研究", 《中国优秀硕士学位论文全文数据库.信息科技辑》 *
谷妤嫔: "医学图像三维重建及交互体视化技术研究", 《中国优秀硕博学士学位论文全文数据库(硕士).信息科技辑》 *

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104915992A (en) * 2015-06-15 2015-09-16 上海应用技术学院 A real-time shadow volume rendering method based on femur CT images
CN105496453A (en) * 2015-11-13 2016-04-20 武汉科技大学 Cattle ovarian follicle ultrasonic monitoring system and monitoring method for same
CN105534476A (en) * 2015-12-05 2016-05-04 新乡医学院第一附属医院 Early detection system for kidney diseases and injuries of department of pediatrics
CN106023300A (en) * 2016-05-09 2016-10-12 深圳市瑞恩宁电子技术有限公司 Body rendering method and system of semitransparent material
CN106023300B (en) * 2016-05-09 2018-08-17 深圳市瑞恩宁电子技术有限公司 A kind of the body rendering intent and system of translucent material
CN107274428A (en) * 2017-08-03 2017-10-20 汕头市超声仪器研究所有限公司 Multi-target three-dimensional ultrasonic image partition method based on emulation and measured data
CN108010115A (en) * 2017-10-30 2018-05-08 中国科学院深圳先进技术研究院 Multiplanar reconstruction method, apparatus, equipment and storage medium for CBCT imagings
CN108010115B (en) * 2017-10-30 2021-02-26 中国科学院深圳先进技术研究院 Multi-plane reconstruction method, device and equipment for CBCT imaging and storage medium
CN107862733A (en) * 2017-11-02 2018-03-30 南京大学 Large scale scene real-time three-dimensional method for reconstructing and system based on sight more new algorithm
CN107862733B (en) * 2017-11-02 2021-10-26 南京大学 Large-scale scene real-time three-dimensional reconstruction method and system based on sight updating algorithm
CN109754869A (en) * 2017-11-08 2019-05-14 通用电气公司 The rendering method and system of the corresponding coloring descriptor of the ultrasound image of coloring
CN109754869B (en) * 2017-11-08 2022-01-04 通用电气公司 Rendering method and system of coloring descriptor corresponding to colored ultrasonic image
CN108053465A (en) * 2017-12-11 2018-05-18 深圳市图智能科技有限公司 A kind of image segmentation result post-processing approach based on volume drawing
CN108354626A (en) * 2018-03-31 2018-08-03 华南理工大学 A variety of MV high clearing systems fast medical ultrasonic image systems based on GPU
WO2019184343A1 (en) * 2018-03-31 2019-10-03 华南理工大学 Gpu-based multiple mv high-definition algorithm fast medical ultrasound imaging system
CN108597012A (en) * 2018-04-16 2018-09-28 北京工业大学 A kind of three-dimensional rebuilding method of the medical image based on CUDA
CN109064543A (en) * 2018-08-30 2018-12-21 十维度(厦门)网络科技有限公司 A kind of graphical textures load rendering method
CN110827401A (en) * 2019-11-15 2020-02-21 张军 Scanning imaging system for interventional therapy
CN110827401B (en) * 2019-11-15 2020-07-10 张军 Scanning imaging system for interventional therapy
CN111466954A (en) * 2020-05-25 2020-07-31 武汉中旗生物医疗电子有限公司 Three-dimensional ultrasonic stereo dissection chart generation method and device
CN112750520A (en) * 2020-12-31 2021-05-04 四川桑瑞思环境技术工程有限公司 Information processing system
CN113781635A (en) * 2021-09-10 2021-12-10 云从科技集团股份有限公司 Medical image projection method, medical image projection apparatus, computer device, and storage medium
CN116805347A (en) * 2023-08-22 2023-09-26 中国电子科技集团公司第十五研究所 Volume texture coating interpolation method based on volume data six-boundary surface geometric configuration
CN116805347B (en) * 2023-08-22 2023-11-10 中国电子科技集团公司第十五研究所 Volume texture coating interpolation method based on volume data six-boundary surface geometric configuration

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