CN105303533A - Ultrasonic image filtering method - Google Patents
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- CN105303533A CN105303533A CN201510736092.4A CN201510736092A CN105303533A CN 105303533 A CN105303533 A CN 105303533A CN 201510736092 A CN201510736092 A CN 201510736092A CN 105303533 A CN105303533 A CN 105303533A
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Abstract
The invention discloses an ultrasonic image filtering method. The method includes the following steps: (1) an Otsu algorithm is adopted to segment an ultrasonic image to be filtered, so as to obtain a binary image; (2) for the binary image, erosion operation is performed first, and then dilation operation is performed; (3) connected area tracking is performed, and all bright spots in the binary image are separated into a plurality of independent connected areas through neighborhood search; (4) according to a preset threshold value, the independent connected area which exceeds the threshold value is retained as a target area; and (5) the target area of the ultrasonic image to be filtered is used as a filtered ultrasonic image, and other areas are set as a background. The method provided by the invention can effectively filter the ultrasonic image, remove noise, and maintain characteristics of original data without occurrence of any deformation of a target, and at the same time, the method is moderate in calculation amount, low in algorithm difficulty and easy to realize.
Description
Technical field
The invention belongs to ultrasonic imaging field, more specifically, relate to a kind of ultrasonoscopy filtering method.
Background technology
Ultrasonic imaging is the important content of medical imaging field, its advantage is radiationless, equipment and use cost low, ultrasonic imaging provides more abundant detailed information, feel intuitively to doctor with by diagnosis person, the professional technique reducing doctor requires and improves the reliability of judgement.Meanwhile, ultrasonoscopy has serious noise, and noise not only affects visual effect, also disturbs the judgement of doctor to a certain extent, and therefore, the filtering of ultrasonoscopy is a hot issue in medical ultrasound image always.Current filtering method is based on MeanShift principle substantially, and by being averaged within the specific limits original image, or the template level and smooth with some does convolution, reaches level and smooth object.Generally speaking, these classic method Problems existing are: the details of easily losing image, and reason is its filtering is by smoothly realizing; Second is the bulk deformation easily causing data model; Last poor robustness, closely related with used parameter.
Summary of the invention
For above defect or the Improvement requirement of prior art, the invention provides a kind of ultrasonoscopy filtering method, its object is to leach speckle noise by Threshold segmentation and connected domain track algorithm being coordinated, solving the technical matters that existing ultrasonic filtering method loses image detail, bulk deformation, poor robustness thus.
For achieving the above object, according to one aspect of the present invention, provide ultrasonoscopy filtering method, comprise the following steps:
(1) adopt Otsu algorithm to split for ultrasonoscopy to be filtered, obtain bianry image;
(2) for the bianry image obtained in step (1), first carry out erosion operation, after carry out dilation operation, obtain the bianry image that target area and noise are separated;
(3) bianry image that the target area obtained in step (2) and noise are separated is carried out connected region tracking, concrete steps are as follows:
Target area is followed the tracks of: for all bright spots in bianry image, be divided into several independent connected regions by neighborhood search;
(4) for the independent connected region obtained in step (3), according to the threshold value preset, reservation exceedes the independent connected region of threshold value as target area;
(5) using the target area of ultrasonoscopy to be filtered as filtered ultrasonoscopy, other regions are set to background.
Preferably, described ultrasonoscopy filtering method, it also comprises step: the smoothing computing in edge of the filtered ultrasonoscopy that step (5) obtains by (6).
Preferably, described ultrasonoscopy filtering method, the described smoothing operation of its step (6) adopts gaussian filtering.
Preferably, described ultrasonoscopy filtering method, its step (3) described neighborhood search concrete steps are as follows:
(3-1) choose arbitrarily a bright spot as Seed Points, marked;
(3-2) search for its neighborhood, if bright spot, then these impact points are all marked;
(3-3) neighborhood of a point that constantly search is labeled, until the point in all labeled neighborhoods of a point has all marked or be dim spot, using these bright spots marked as an independent connected region;
(3-4) repeated execution of steps (3-1)-(3-3) in remaining bright spot, until all bright spots are labeled, namely all bright spots are divided in some independent connected regions.
In general, the above technical scheme conceived by the present invention compared with prior art, can obtain following beneficial effect:
1, compared with noise, artifact, the target in ultrasonoscopy be brighter relatively, so, by Threshold segmentation, can roughly noise and artifact be separated with target.
2, "ON" operation is carried out to bianry image, as far as possible by some little targets or press close to the noise of target and target area disconnects.
3, by search to impact point neighborhood, using all be communicated with impact point o'clock to gather as one, thus target, noise and artifact are separated, think that the larger several targets of volume are the ultrasonic imaging targets for reality, other regards as is noise and artifact.
4, in original image, the gray scale of non-imaged target being composed is 0, and the bright spot of imageable target gives its original gray-scale value, and the dim spot of imageable target then gets the average of non-zero point in its neighborhood, obtains filtered image.Therefore, this filtering method does not change the gray scale of target in image, but background, artifact and noise is separated with target area as far as possible, therefore the improper feature that can keep raw data of filtered image, and the distortion of target can not be there is.
To sum up, the inventive method effectively can carry out filtering to ultrasonoscopy, cancelling noise, and keep the feature of raw data, and any deformation can not occur target, meanwhile, this method calculated amount is moderate, and algorithm difficulty is little, realizes easily.
Accompanying drawing explanation
Fig. 1 filtering process flow diagram of the present invention;
Three-dimensional medical ultrasonic image volume rendered images before Fig. 2 filtering;
Three, three-D ultrasound data center cross-section image before Fig. 3 filtering;
Three-dimensional medical ultrasonic image volume rendered images after Fig. 4 filtering;
Three, three-D ultrasound data center cross-section image after Fig. 5 filtering.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.In addition, if below in described each embodiment of the present invention involved technical characteristic do not form conflict each other and just can mutually combine.
Ultrasonic imaging has clinical value very widely, and noises a large amount of in image not only have impact on the effect of vision, and may affect the judgement of doctor to imageable target.Therefore the filtering of ultrasonoscopy is the study hotspot of association area always, the method of this method is no longer based on MeanShift principle, but the object and background in ultrasonoscopy, noise and artifact are separated, then non-targets of interest all being regarded as is background, finally utilizes traditional gaussian filtering to process image.
Ultrasonoscopy filtering method provided by the invention, comprises the following steps:
(1) adopt Otsu algorithm to split for ultrasonoscopy to be filtered, obtain bianry image; Generally speaking, it is highlighted that target presents, and background is relatively dark, therefore bright point thinks the point on target image.Preferred employing following steps, split:
Raw ultrasound image approximate is divided into two classes, target and background: set the gray level of image as L, gray scale is that counting of the pixel of i is set to N
i.Gray-scale value is the probability that i occurs is P
i=N
i/ N.So, find a thresholding t, image be divided into and make the gray variance between two class targets maximum.In image, gray-scale value is greater than the some assignment of threshold value is 255, and all the other are 0.
(2) for the bianry image obtained in step (1), first carry out erosion operation, after carry out dilation operation, different targets is separated, obtains the bianry image that target area and noise are separated;
Utilize corrosion dilation operation little target to be separated from general objective, wherein erosion operation is a kind of method eliminating frontier point, does AND-operation by structural element template and bianry image, Er value Tu Xiang Of-thin mono-circle made.Dilation operation and erosion operation similar, difference is that structural element template and image are done OR operation, and the border of object is externally expanded.Owing to the object of the invention is to carry out filtering to ultrasonoscopy, therefore take the strategy first corroding rear expansion, also referred to as being opening operation in mathematical morphology.
(3) bianry image that the target area obtained in step (2) and noise are separated is carried out connected region tracking, concrete steps are as follows:
Target area is followed the tracks of: for all bright spots in bianry image, be divided into several independent connected regions by neighborhood search.
For realizing said process, can following steps be taked:
(3-1) choose arbitrarily a bright spot as Seed Points, marked;
(3-2) search for its neighborhood, if bright spot, then these impact points are all marked;
(3-3) neighborhood of a point that constantly search is labeled, until the point in all labeled neighborhoods of a point has all marked or be dim spot, using these bright spots marked as an independent connected region;
(3-4) repeated execution of steps (3-1)-(3-3) in remaining bright spot, until all bright spots are labeled, namely all bright spots are divided in some independent connected regions.
(4) for the independent connected region obtained in step (3), according to the threshold value preset, reservation exceedes the independent connected region of threshold value as target area;
Threshold value is arranged, and according to the character of image itself, can arrange threshold value or arrange threshold value according to area rank according to size.
(5) using the target area of ultrasonoscopy to be filtered as filtered ultrasonoscopy, other regions are set to background.
(6) the smoothing computing in edge of filtered ultrasonoscopy step (5) obtained, preferably adopts gaussian filtering.Utilize Gaussian function to generate a certain size template, carry out convolution by template and above-mentioned image, obtain the result images of gaussian filtering.
Be below embodiment:
A kind of ultrasonoscopy filtering method, is applied to three-dimensional ultrasound pattern filtering:
(1) Threshold segmentation of three-dimensional ultrasound pattern, if the size of input 3-D view is nwidth*nheight*ndepth, the gray level of image is L=256, and gray scale is that counting of the pixel of i is set to N
i, nwidth*nheight*ndepth=N
0+ N
1+ ...+N
l-1.Gray-scale value is the probability that i occurs is P
i=N
i/ N.So, find a thresholding t, 3-D view be divided into bright target c
1with dark background c
2, then the relation of inter-class variance σ and t is σ=a
1* a
2(u
1-u
2) ^2, in formula, a
1, a
2for class c
1, c
2the ratio of the total area, a
1=sum (P
i) i>t, a
2=1-a
1; u
1, u
2be respectively the average of two classes, u
1=sum (i*P
i)/a
1i<t, u
2=sum (i*P
2)/a
2, i>=t, select an optimum thresholding t, the inter-class variance made is maximum.After calculating threshold value, in original image, gray scale is greater than the tax of threshold value is 255, and other tax is 0, generates bianry image.
(2) bianry image is corroded and expansive working.In the method, the operation of corrosion is: in 3 × 3 × 3 windows centered by each voxel in two-value volume data, judges whether that gray-scale value is the point of 0, if had, is then 0 by current point assignment; The operation of expanding is: in 3 × 3 × 3 windows centered by each voxel in two-value volume data, judge whether that gray-scale value is the point of 255, if had, is then 255 by current point assignment.Constantly carry out corroding and expansive working, in the 3-D view of binaryzation, form the region that the gray-scale value with some is multiple connections of 255.
(3) in bianry image, any selection gray-scale value is the impact point (point close to 3-D view center is selected in general recommendations) of 255, join a set, search in its 26 neighborhood whether have gray-scale value be 255 point, if had, to join in set, simultaneously, point in set is marked, if the 26 neighborhoods all searched mistake of certain point, be then labeled as 1, otherwise be 0 in set; Next step be exactly select arbitrarily in a set one be labeled as 0 point, search in its 26 neighborhood whether have bright spot, and bright spot joined in a set, be then labeled as 1; Then, constantly from a set, selected marker value is the point of 0, and constantly its neighborhood of search is to repeat said process, and in some set, all points are all marked as till 1.
(4) completing steps (3) is equivalent to obtain a goal set be communicated with, and the image of actual binaryzation, very multiply connected goal set may be had, so, be select a point (point be not labeled) arbitrarily in the point of 255 from remaining gray-scale value, repeat the process of step (3), obtain corresponding connectivity points set.Continuous execution (3)-(4), until points all in bianry image is all labeled.
(5), in the some set obtained in step (4), if the volume of some set is less than certain quantity, then these gray scales put all being composed is 0.
(6) contrast the bianry image of original three-dimensional image and step (5), the gray-scale value of voxel outside bianry image targets of interest is 0, then being composed by the gray-scale value of respective pixel in original image is 0; The gray-scale value of voxel in bianry image targets of interest is 255, then give the gray-scale value of correspondence position in its original image, and the gray-scale value of voxel in bianry image targets of interest is 0, then give the average of non-zero point in its original image 26 neighborhood.
(7) utilize Gaussian template to carry out filtering to step (6) image, be specially: first utilize dimensional Gaussian template to be { 1,2,3,2,1; 2,5,6,5,2; 3,6,8,6,3; 2,5,6,5,2; 1,2,3,2,1}, carries out two-dimensional filtering to the 5*5 image in 5*5*5 window, generates the data of 5*1; Then, { 3,6,8,6,3} carries out convolution to recycling again; Obtain the filter result of window center point.
Those skilled in the art will readily understand; the foregoing is only preferred embodiment of the present invention; not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.
Claims (4)
1. a ultrasonoscopy filtering method, is characterized in that, comprises the following steps:
(1) adopt Otsu algorithm to split for ultrasonoscopy to be filtered, obtain bianry image;
(2) for the bianry image obtained in step (1), first carry out erosion operation, after carry out dilation operation, obtain the bianry image that target area and noise are separated;
(3) bianry image that the target area obtained in step (2) and noise are separated is carried out connected region tracking, concrete steps are as follows:
Target area is followed the tracks of: for all bright spots in bianry image, be divided into several independent connected regions by neighborhood search;
(4) for the independent connected region obtained in step (3), according to the threshold value preset, reservation exceedes the independent connected region of threshold value as target area;
(5) using the target area of ultrasonoscopy to be filtered as filtered ultrasonoscopy, other regions are set to background.
2. ultrasonoscopy filtering method as claimed in claim 1, it is characterized in that, described method also comprises step: the smoothing computing in edge of the filtered ultrasonoscopy that step (5) obtains by (6).
3. ultrasonoscopy filtering method as claimed in claim 2, is characterized in that, the described smoothing operation of step (6) adopts gaussian filtering.
4. ultrasonoscopy filtering method as claimed in claim 1, it is characterized in that, step (3) described neighborhood search concrete steps are as follows:
(3-1) choose arbitrarily a bright spot as Seed Points, marked;
(3-2) search for its neighborhood, if bright spot, then these impact points are all marked;
(3-3) neighborhood of a point that constantly search is labeled, until the point in all labeled neighborhoods of a point has all marked or be dim spot, using these bright spots marked as an independent connected region;
(3-4) repeated execution of steps (3-1)-(3-3) in remaining bright spot, until all bright spots are labeled, namely all bright spots are divided in some independent connected regions.
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