CN105520712B - A kind of gynecatoptron image intelligent acquisition appraisal procedure and device - Google Patents
A kind of gynecatoptron image intelligent acquisition appraisal procedure and device Download PDFInfo
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Abstract
The present invention provides a kind of acquisition of gynecatoptron image intelligent and appraisal procedures, which comprises the following steps: suspected lesion region is chosen in gynecatoptron image；According to the amplification factor of suspected lesion region gynecatoptron described in the position adjust automatically in gynecatoptron image；Acquire gynecatoptron image.The present invention also provides a kind of intelligent gynecatoptron Image Acquisition and assessment devices, which is characterized in that including image-display units, suspected lesion area selecting unit, amplification factor control unit, image acquisition units.Intelligence gynecatoptron Image Acquisition and appraisal procedure provided by the invention, amplification factor can be automatically adjusted, under the premise of not moving lens, pass through automatic zoom and zoom mode, optimal amplification factor is chosen, the clarity of uterine neck lesions position is utmostly improved, reduces doctor's manual focus operations, it is more convenient, fast.
Description
Technical field
The present invention relates to gynaecology's technical field of medical equipment more particularly to a kind of gynecatoptron image intelligent to acquire appraisal procedure
And device.
Background technique
Cervical carcinoma is unique specific cancer of the cause of disease in all cancerous lesions of the current mankind, and can uniquely be expected to pass through
The cancer that artificial prevention is reduced or eliminated.Vaginoscopy can be found that cervical erosion, cervical polyp, cervical intraepithelial neoplasia sample disease
Change, cervical carcinoma, vaginitis, vulva, vagina or the weak and incompetent tumor disease of uterine neck, poison infection and subclinical parillomarvirus infections.Gynecatoptron
Check not only diagnose cervix early carcinomatous change and distinguish tumour and in terms of have application value, but also in terms for the treatment of,
Especially there is special applications value in the treatment of cervical intraepithelial neoplasia (CIN).Because gynecatoptron can see epithelium of cervix uteri variation
Location and range, the video image of gynecatoptron or Video Image acquisition and storage to the tracing studys of cervical lesions very
It is important.
During vaginoscopy, the prior art is exactly gynecatoptron acquired image of the doctor according to acquisition, uses meat
Eye goes variation of the observation epithelium of cervix uteri after using physiological saline, 5% acetum and 5% Dobell's solution, to gynecatoptron institute
The image of acquisition carries out interpretation and assessment.But understand that the gynaecologist of vaginoscopy and diagnosis is insufficient at present, while in palace
Neck cancer lacks the diagnostic criteria of specification in checking, thus, it not can guarantee grassroots medical worker and correctly check operation, mistake
Image analysis will lead to the abnormal position biopsy of mistake, thus can mistaken diagnosis, fail to pinpoint a disease in diagnosis or excessive biopsy.In addition, due to not quantifying
Standard, ununified evaluation criteria are assessed the image for checking and acquiring even if collecting expert, for same patient
Image, may different expert can all have different assessment results (influence by subjective factor), thus impact evaluation
Accuracy and consistency.
Summary of the invention
In view of this, the present invention is intended to provide a kind of gynecatoptron image intelligent acquisition appraisal procedure and device, can assist in
Doctor more accurately assesses the lesion type of gynecatoptron image.
In order to achieve the above object, the present invention is achieved through the following technical solutions: a kind of gynecatoptron image intelligent acquisition
Appraisal procedure, which comprises the following steps:
Step A1, suspected lesion region is chosen in gynecatoptron image；
Step A2, putting according to suspected lesion region gynecatoptron described in the position adjust automatically in gynecatoptron image
Big multiple；
Step A3, gynecatoptron image is acquired.
Further, in step A2:
If the gynecatoptron image pixel size M*N, origin (0,0) is located at the gynecatoptron image upper left corner, described to doubt
It is [(x1, y1), (x2, y2)], the then amplification of gynecatoptron described in adjust automatically like position of the lesion region in gynecatoptron image
Multiple Δ β are as follows:
Δ β=1/ [1-2*min (x1/M, y1/N, (M-x2)/M, (N-y2)/N)]-a%, a >=0, Δ β > 0.
Preferential, after step A3 further include:
Step A4, typical suspected lesion region is chosen in the gynecatoptron image described in step A3, and is analyzed described typical doubtful
Like the lesion type of lesion region；
The size in the typical suspected lesion region of the selection is one of several area sizes of agreement, chooses and analyzes
The mode in typical suspected lesion region includes any combination of following manner:
Area of computer aided chooses and analysis；
Operator voluntarily chooses and analyzes.
Further, after step A4 further include:
Step A5, gynecatoptron image is chosen in standard gynecatoptron picture library to compare, the standard gynecatoptron picture library
Gynecatoptron image includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
Preferential, the standard that gynecatoptron image is chosen in standard gynecatoptron picture library includes one of following standard:
(1) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size
It is identical as the typical suspected lesion area image size；
(2) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image amplifies
Multiple and the typical suspected lesion area image amplification factor are identical or closest.
The present invention also provides a kind of gynecatoptron image intelligents to acquire assessment device, which is characterized in that shows including image single
Member, suspected lesion area selecting unit, amplification factor control unit, image acquisition units；
Described image display unit is used for real-time display gynecatoptron image；
The suspected lesion area selecting unit is for choosing suspected lesion region in the gynecatoptron image；
The amplification factor control unit is calculated for the position according to the suspected lesion region in gynecatoptron image
And the amplification factor of vagina lens head described in adjust automatically；
Described image acquisition unit is for acquiring gynecatoptron image.
It further, further include typical suspected lesion area selecting unit, for choosing typical suspected lesion region, and it is automatic
The size for adjusting the typical suspected lesion region is one of several area sizes of agreement.
It further, further include typical suspected lesion zone analysis unit, for analyzing the lesion in typical suspected lesion region
Type.
It further, further include standard gynecatoptron picture library storage unit, for storing standard gynecatoptron image, the standard yin
Road mirror image has the feature that
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
Further, further include comparison display unit, carried out pair for choosing gynecatoptron image in standard gynecatoptron picture library
Than display, the gynecatoptron image of the standard gynecatoptron picture library includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement；
The standard that gynecatoptron image is chosen in standard gynecatoptron picture library includes one of following standard:
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size and institute
It is identical to state typical suspected lesion area image size；
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image magnification
It is identical or closest as the typical suspected lesion area image amplification factor.
The present invention has the following advantages and effects with respect to the prior art:
(1) gynecatoptron image intelligent acquisition provided by the invention and appraisal procedure, can automatically adjust amplification factor, not
Under the premise of moving lens, by automatic zoom and zoom mode, optimal amplification factor is chosen, cervix disease is utmostly improved
The clarity at stove position reduces doctor's manual focus operations, more convenient, quick.
(2) gynecatoptron image intelligent provided by the invention acquisition and appraisal procedure, by computer-aided diagnosis technology and
Standard gynecatoptron picture library can effectively improve different doctors to the diagnosis compatibility of same sub-picture with comparison is shielded；It can also be used as one
Kind gynecatoptron Training and Learning tool helps the overall cognitive level for improving medical profession to gynecatoptron image.
Detailed description of the invention
The present invention is described in detail by following preferred embodiments and attached drawing for ease of explanation,.
Fig. 1 is the acquisition of embodiment gynecatoptron image intelligent and estimation flow schematic diagram；
Fig. 2 is that embodiment gynecatoptron image magnification calculates thinking schematic diagram one；
Fig. 3 is that embodiment gynecatoptron image magnification calculates thinking schematic diagram two；
Fig. 4 is that embodiment gynecatoptron image magnification calculates thinking schematic diagram three；
Fig. 5 is that embodiment gynecatoptron image magnification calculates thinking schematic diagram four.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited
In this.
Embodiment one
Shown in referring to Fig.1, a kind of gynecatoptron image intelligent acquisition appraisal procedure, which comprises the following steps:
Step A1, suspected lesion region is chosen in gynecatoptron image；
Step A2, putting according to suspected lesion region gynecatoptron described in the position adjust automatically in gynecatoptron image
Big multiple；
Step A3, gynecatoptron image is acquired.
It should be noted that the innovative point of the present embodiment is described in step A2: according to the suspected lesion region in yin
The amplification factor of gynecatoptron described in position adjust automatically in road mirror image, this method can automatically adjust amplification factor,
Not under the premise of moving lens, by autozoom mode, optimal amplification factor is chosen, utmostly improves uterine neck lesion portion
The clarity of position reduces doctor's manual focus operations, more convenient, fast.In the prior art, in order to obtain area-of-interest
The clearest gynecatoptron image in (suspected lesion region), requires to obtain amplified original image by way of focusing.It adjusts
There are two types of burnt mode is general, manual focusing and selection gear automatic focusing.The former is that focal length is manually operated when seeing, Hou Zhetong
Selection gear is crossed by equipment automatic focusing.Both modes are all not intuitive enough, are all by adjusting seeing that image is again after focal length
It is no suitable, it generally requires adjustment repeatedly, can just choose most suitable gear.Adjust automatically gynecatoptron puts described in the present embodiment
Big multiple is according to the times magnification of suspected lesion region gynecatoptron described in the position adjust automatically in gynecatoptron image
Number operates more intuitively, conveniently.
Referring to shown in Fig. 2, further, in step A2:
If the gynecatoptron image pixel size M*N, origin (0,0) is located at the gynecatoptron image upper left corner, described to doubt
It is [(x1, y1), (x2, y2)], the then amplification of gynecatoptron described in adjust automatically like position of the lesion region in gynecatoptron image
Multiple Δ β are as follows:
Δ β=1/ [1-2*min (x1/M, y1/N, (M-x2)/M, (N-y2)/N)]-a%, a >=0, Δ β > 0.
It should be noted that the present embodiment is adjusted automatically according to position of the suspected lesion region in gynecatoptron image
The amplification factor of the whole gynecatoptron, under the premise of not moving gynecatoptron position, by operator choose area-of-interest come
The focal length for determining camera lens adjustment, obtains maximum suspected lesion area image amplification factor.
In order to illustrate the origin of above-mentioned formula and the determination thinking of the present embodiment amplification factor, referring to shown in Fig. 2~4.
Amplification factor described in the present embodiment refers to that line segment amplification factor, the i.e. line segment of original image α cm length are shown after the amplification of β multiple
The length shown is α * β cm.If expecting image area amplification factor, amplification factor described in the present embodiment need to be only squared i.e.
It can.
In the present embodiment, if gynecatoptron image left upper apex O, as origin (0,0), bottom right vertex are set as S (M, N),
Suspected lesion region (A1, A2) left upper apex is set as A1 (x1, y1), and bottom right vertex is set as A2 (x2, y2).The dotted line frame of Fig. 2~4 institute
Show that image-region (O ', S ') is the position according to suspected lesion region (A1, A2) in the picture, the image range that will amplify,
This image range just includes suspected lesion region (A1, A2), and Aspect Ratio is consistent with gynecatoptron image Aspect Ratio.
Can be seen that by Fig. 2~4, an equal amount of suspected lesion region A1 (x1, y1) in the picture different location when, put
Big multiple is not quite similar.Concrete thought is: finding suspected lesion region (A1, A2) first apart from the edge gynecatoptron image (O, S)
Beyond recently, then on the basis of this one side, the image range to be amplified of determination (O ', S '), i.e., in figure shown in dotted line
Region.It is more slightly larger than suspected lesion region (A1, A2) if necessary, it can suitably increase some amplification factors.
It is analyzed through above-mentioned thinking, amplification factor Δ β are as follows:
Δ β=1/ [1-2*min (x1/M, y1/N, (M-x2)/M, (N-y2)/N)]-a%, a >=0, Δ β > 0.
As preferential embodiment, after step A3 further include:
Step A4, typical suspected lesion region is chosen in the gynecatoptron image described in step A3, and is analyzed described typical doubtful
Like the lesion type of lesion region；
The size in the typical suspected lesion region of the selection is one of several area sizes of agreement, chooses and analyzes
The mode in typical suspected lesion region includes any combination of following manner:
Area of computer aided chooses and analysis；
Operator voluntarily chooses and analyzes.
In the present embodiment, step A4 is in order to which lesion of the person of being more convenient to operate to suspected lesion region confirms.Existing
In technology, the comparison between gynecatoptron image is often the comparison of whole picture gynecatoptron image, and exists to interested diseased region
Shared ratio is relatively small in entire image, is easy for being ignored in this way or is inconvenient to compare.The present embodiment will be interested
Diseased region extracts independent display, helps fast and accurately to confirm the lesion in suspected lesion region.
In the present embodiment, due to only selecting that analysis suspected lesion region compares, how accurately to choose doubtful
Like lesion region, determines that can lesion accurately and rapidly be made a definite diagnosis, can neither fail to pinpoint a disease in diagnosis, it can not mistaken diagnosis.It present embodiments provides
Two ways: (1) operator voluntarily chooses and analyzes；(2) area of computer aided is chosen and is analyzed.Firstly, for gynecatoptron figure
As for, due to its professional and intrinsic anatomical physiology characteristic, doubtful lesion region often has its distinctive rule,
And if this rule is applied alone traditional image processing method to handle, recognizer is just excessively complicated, operation efficiency and accurate
It spends also not high.If chosen by the operator for having professional knowledge, suspected lesion region, Er Qie cracking can be found
Operator can choose suspected lesion region when acquiring gynecatoptron image using equipment in passing, this complies fully with medicine behaviour
Make process, too many inconvenience will not be generated.What makes more sense is that medical worker can choose very typical doubtful disease as needed
Become region, is also easier to find most like standard gynecatoptron image from gynecatoptron picture library, it is faster more acurrate to be compared
And confirmation.
Suspected lesion region, then the comparison through standard gynecatoptron image are first chosen by medical worker's subjectivity, it can be obvious
Reduce the false positive rate of gynecatoptron diagnostic imaging, i.e. misdiagnosis rate.It, can but before the subjectivity just because of medical worker is chosen at
It avoids due to caused by missing inspection " false negative ".For this purpose, the present embodiment, which also provides one kind, chooses suspected lesion by computer intelligence
The mode in region, can be by existing provincial characteristics matching algorithm, this needs more complicated operation certainly.It may be noted that
Be, by craft or computer intelligence both choose suspected lesion regions in the way of, the deficiency that both can make up.But as
The choosing of any or both of which is selected, operator can select according to actual needs.
Further, after step A4 further include:
Step A5, gynecatoptron image is chosen in standard gynecatoptron picture library to compare, the standard gynecatoptron picture library
Gynecatoptron image includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
Further, the standard that gynecatoptron image is chosen in standard gynecatoptron picture library includes one of following standard:
(1) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size
It is identical as the typical suspected lesion area image size；
(2) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image amplifies
Multiple and the typical suspected lesion area image amplification factor are identical or closest.
In the present embodiment step 4,5, the typical suspected lesion region of the selection is sized to the several of agreement
One of a area size, and the gynecatoptron image of the standard gynecatoptron picture library is sized to several regions of the agreement
The purpose of one of size is convenience and accuracy in order to increase image comparison identification.Two kinds of comparisons provided in this embodiment
Mode, it is identical (may be by different amplification factors) that one is both images of comparison sizes, a kind of lesion actual size
Identical or approximate (may be different image size), being supplied to operator, more intuitive information is used to compare.
The present embodiment also provides a kind of gynecatoptron image intelligent acquisition assessment device, which is characterized in that shows including image
Unit, suspected lesion area selecting unit, amplification factor control unit, image acquisition units；
Described image display unit is used for real-time display gynecatoptron image；
The suspected lesion area selecting unit is for choosing suspected lesion region in the gynecatoptron image；
The amplification factor control unit is calculated for the position according to the suspected lesion region in gynecatoptron image
And the amplification factor of vagina lens head described in adjust automatically；
Described image acquisition unit is for acquiring gynecatoptron image.
If the gynecatoptron image pixel size M*N, origin (0,0) is located at the gynecatoptron image upper left corner, described to doubt
It is [(x1, y1), (x2, y2)], the then amplification of gynecatoptron described in adjust automatically like position of the lesion region in gynecatoptron image
Multiple Δ β are as follows:
Δ β=1/ [1-2*min (x1/M, y1/N, (M-x2)/M, (N-y2)/N)]-a%, a >=0, Δ β > 0.
It further, further include typical suspected lesion area selecting unit, for choosing typical suspected lesion region, and it is automatic
The size for adjusting the typical suspected lesion region is one of several area sizes of agreement.
It further, further include typical suspected lesion zone analysis unit, for analyzing the lesion in typical suspected lesion region
Type.
It further, further include standard gynecatoptron picture library storage unit, for storing standard gynecatoptron image, the standard yin
Road mirror image has the feature that
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
Further, further include comparison display unit, carried out pair for choosing gynecatoptron image in standard gynecatoptron picture library
Than display, the gynecatoptron image of the standard gynecatoptron picture library includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement；
The standard that gynecatoptron image is chosen in standard gynecatoptron picture library includes one of following standard:
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size and institute
It is identical to state typical suspected lesion area image size；
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image magnification
It is identical or closest as the typical suspected lesion area image amplification factor.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention,
It should be equivalent substitute mode, be included within the scope of the present invention.
Claims (9)
1. a kind of gynecatoptron image intelligent acquires appraisal procedure, which comprises the following steps:
Step A1, suspected lesion region is chosen in gynecatoptron image；
Step A2, the amplification factor of the position adjust automatically gynecatoptron according to the suspected lesion region in gynecatoptron image；
In step A2:
If the gynecatoptron image pixel size M*N, origin (0,0) is located at the gynecatoptron image upper left corner, the doubtful disease
Become position of the region in gynecatoptron image as [(x1, y1), (x2, y2)], then the amplification factor of gynecatoptron described in adjust automatically
Δ β are as follows:
Δ β=1/ [1-2*min (x1/M, y1/N, (M-x2)/M, (N-y2)/N)]-a%, a >=0, Δ β > 0；
Step A3, gynecatoptron image is acquired.
2. gynecatoptron image intelligent acquires appraisal procedure according to claim 1, which is characterized in that also wrapped after step A3
It includes:
Step A4, typical suspected lesion region is chosen in the gynecatoptron image described in step A3, and analyzes the doubtful disease of typical case
Become the lesion type in region；
The size in the typical suspected lesion region of the selection is one of several area sizes of agreement, chooses and analysis is typical
The mode in suspected lesion region includes any combination of following manner:
Area of computer aided chooses and analysis；
Operator voluntarily chooses and analyzes.
3. gynecatoptron image intelligent acquires appraisal procedure according to claim 2, which is characterized in that also wrapped after step A4
It includes:
Step A5, it chooses gynecatoptron image in standard gynecatoptron picture library to compare, the vagina of the standard gynecatoptron picture library
Mirror image includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
4. gynecatoptron image intelligent acquires appraisal procedure according to claim 3, which is characterized in that in standard gynecatoptron picture library
The middle standard for choosing gynecatoptron image includes one of following standard:
(1) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size and allusion quotation
Type suspected lesion area image size is identical；
(2) selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image magnification
It is identical or closest as typical suspected lesion area image amplification factor.
5. a kind of gynecatoptron image intelligent acquisition assessment device for implementing claim 1 the method, which is characterized in that including figure
As display unit, suspected lesion area selecting unit, amplification factor control unit, image acquisition units；
Described image display unit is used for real-time display gynecatoptron image；
The suspected lesion area selecting unit is for choosing suspected lesion region in the gynecatoptron image；
The amplification factor control unit calculates simultaneously certainly for the position according to the suspected lesion region in gynecatoptron image
The amplification factor of dynamic adjustment vagina lens head；
Described image acquisition unit is for acquiring gynecatoptron image.
6. gynecatoptron image intelligent acquisition assessment device according to claim 5, which is characterized in that further include typical doubtful
Lesion region selecting unit, for choosing typical suspected lesion region, and typical case's suspected lesion region described in adjust automatically is big
Small one of several area sizes for agreement.
7. gynecatoptron image intelligent acquisition assessment device according to claim 6, which is characterized in that further include typical doubtful
Lesion region analytical unit, for analyzing the lesion type in typical suspected lesion region.
8. gynecatoptron image intelligent acquisition assessment device according to claim 7, which is characterized in that further include standard vagina
Mirror picture library storage unit, for storing standard gynecatoptron image, the standard gynecatoptron image is had the feature that
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement.
9. gynecatoptron image intelligent acquisition assessment device according to claim 8, which is characterized in that further include comparison display
Unit compares display, the yin of the standard gynecatoptron picture library for choosing gynecatoptron image in standard gynecatoptron picture library
Road mirror image includes following characteristics:
With the lesion type made a definite diagnosis；
Image size is one of several area sizes of the agreement；
It includes one of following standard that the standard of gynecatoptron image is chosen in standard gynecatoptron picture library:
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image size and typical case doubt
It is identical like lesion region image size；
Selection is identical with the lesion type in the typical suspected lesion region of the analysis, and its image magnification and allusion quotation
Type suspected lesion area image amplification factor is identical or closest.
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| CN107220975B (en) | 2017-07-31 | 2018-03-09 | 合肥工业大学 | Uterine neck image intelligent auxiliary judgment system and its processing method |
| CN108917548B (en) * | 2018-04-19 | 2020-05-19 | 中国航发南方工业有限公司 | Turbine blade profile detection method and measuring device |
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| CN103249349A (en) * | 2010-12-02 | 2013-08-14 | 奥林巴斯株式会社 | Endoscopic image processing apparatus and program |
| CN103975364A (en) * | 2011-12-05 | 2014-08-06 | 皇家飞利浦有限公司 | Selection of images for optical examination of the cervix |
| CN104840177A (en) * | 2015-05-12 | 2015-08-19 | 汪子锋 | Multi-functional diagnosis and operation device for gynecology |
| CN107750451A (en) * | 2015-07-27 | 2018-03-02 | 三星电子株式会社 | For stablizing the method and electronic installation of video |
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