CN104809331A - Method and system for detecting radiation images to find focus based on computer-aided diagnosis (CAD) - Google Patents
Method and system for detecting radiation images to find focus based on computer-aided diagnosis (CAD) Download PDFInfo
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- CN104809331A CN104809331A CN201510130828.3A CN201510130828A CN104809331A CN 104809331 A CN104809331 A CN 104809331A CN 201510130828 A CN201510130828 A CN 201510130828A CN 104809331 A CN104809331 A CN 104809331A
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- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000004195 computer-aided diagnosis Methods 0.000 title claims abstract description 12
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- 208000020816 lung neoplasm Diseases 0.000 claims abstract description 12
- 206010058467 Lung neoplasm malignant Diseases 0.000 claims abstract description 11
- 201000005202 lung cancer Diseases 0.000 claims abstract description 11
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- 238000012544 monitoring process Methods 0.000 abstract description 33
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Abstract
Provided are a method and system for detecting radiation images to find focus based on computer-aided diagnosis (CAD) which is a method and system for using a computer-aided diagnosis technology to detect and display (mark) a series of diseases including lung cancer tumors, calcified focus and/or lumps on digital X-ray pictures. The digital X-ray pictures are automatically processed through a computer-aided diagnosis system at different stages so as to produce various middle results. Original images are also simultaneously sent to an operator to be subjected to analysis for artificial diagnosis. Middle results from the computer-aided diagnosis system at all processing stages are optimally compared with an artificial diagnosis result so as to produce an optimal result. The processing process relates to automatic detection and quality control monitoring. The processing results refer to the results of the computer-aided diagnosis system and CAD middle results or non-imaging information from original digital X-ray pictures.
Description
1. technical field
This invention is the systems approach about computer intelligence processing X-ray photo, and more detailed saying is the pathological tissues about detecting in X-ray photograph, and such as lung cancer bunch, calcification and lump, consider the monitored results from other CAD system and/or radiologist simultaneously
Current generally acknowledge the most universal in the world, economical is diagnose the early stage of lung cancer by chest X-light ray image (mainly with the digitized X-light ray image that CR/DR technology produces) with traditional method of lung cancer diagnosis.But because these inspections are merely able to provide image the most intuitively; be limited to the direct display effect of inspection and the own level of image doctor and its experience; the reasons such as human eye resolution characteristic and human negligence; enough the more information that image picture comprises could not be used fully; as as the small lesion/lesser tubercle judging cancer, doctor understands skip 30%-55% usually by traditional read tablet mode.Doctor needs a kind of senior ancillary technique to be integrated by various fox message, and after treatment, to tumour, tubercle, cavity, inflammation, and the pathology such as fiberization can improve recall rate to radioscopic image.This computer-aided diagnosis technology (cad technique) identifiable design goes out the diagnostic message that human eye can not identify, can be used as second eyes of doctor, make the rate of missed diagnosis of doubtful lung cancer focus have dropped more than 60%, play a part more and more important in the early diagnosis process of lung cancer.
2. background technology
For breast cancer detection, mammary gland radiation detection method and physical detection are current breast cancer examination standards.Although breast x optical test is the technology that a ripeness standard is crossed, still have the women of 10% to 30% to be diagnosed as breast cancer, their state of an illness does not show on breast x photoimaging.In addition, only have the patient of 10-20% to carry out biopsy based on X-ray photograph and find cancer.It is worth mentioning that, malignant tumour is missed possibility in breast x optical test probably has 2/3rds.Detect the possibility of makeing mistakes and owing to several factor, can comprise picture quality not good, improperly scanning position, the incorrect deciphering of doctor, mammary gland fibroglandular tissue is fuzzy, the limitation of radiograph technology, eye fatigue or carelessness.
CAD system can be used for aiding in early days now widely, and the stage checks out above disease.Market exists several kinds of systems and can detect breast cancer on mammograph, the Second Look of such as iCAD company, the ImageChecker of Hologic company, the Kodak Mammography CAD Engine. of Carestream Health company is a kind of in addition shines the system detecting lung cancer omen, from OnGuard company by chest.
In practice, CAD puts into practice in such a way.Patient arrives photo place.Staff uses image documentation equipment to take medical picture.These figure sector-meetings are placed into CAD system.CAD system can be analyzed picture and Shows Picture on paper or on electronic equipment and mark potential affected areas.Subsequently, when radiating doctor and interpreting blueprints for patient, CAD can identify more how possible affected areas.Effect of CAD is to ensure that doctor can notice the possible affected areas that he does not consider at the beginning.
3. summary of the invention
Object of this invention is to provide a kind of more perfect mode and system from X-ray photograph to detect Microcalcification stove bunch and lump.
For realizing detection calcification bunch and these targets of lump, this invention can carry out detection by completing five steps to X-ray photograph (obtain, pre-service, preselected, feature extraction, classification).
Monitor staff is by generating diagnostic result after inspection X-ray exograph X and indirect CAD result and final CAD result.Diagnostic result can carry out contrasting with indirect CAD result and obtain more perfect process after a while in ensuing CAD process.Following diagnostic result can contrast with CAD net result more further, and these results finally can provide reliable reference for operating personnel.
The CAD system of this invention can indicate when analysis x-ray photo accurately clearly may affected areas.
This invention generates monitored results according to CAD result.
Final CAD monitored results comprises CAD net result and last diagnostic result.
Last diagnostic result will have low-down false positive can't occur any exception.
Professional operator obtains data and rejects false possibility drawing legitimate reading thus generating monitoring CAD result original digital image data input system or from CAD before.These CAD monitored results comprise the result of original CAD result and monitoring generation
Therefore, the mode and the system that are to provide a convenience and high accuracy can make radiologist rely on CAD system result to identify affected areas order of the present invention.
4. accompanying drawing explanation
Fig. 1 indicates a kind of diagnostic procedure employing monitoring CAD mode auxiliary detection breast cancer
Fig. 2 indicates a kind of monitoring CAD system and supervises executable mode.
Fig. 3 is the structural drawing that a CAD cellular system is formed
Fig. 4 is the structural drawing of a monitoring unit System's composition
Fig. 5 is the structural drawing of an inspection unit, and then operating personnel can be sent to pretreatment unit Fig. 2 result from image input units reception result at this
Fig. 6 is the structural drawing of an inspection unit, and then operating personnel can be sent to pre-selection unit Fig. 2 result from pretreatment unit reception result at this.
Fig. 7 is the structural drawing of an inspection unit, and then operating personnel can be sent to result the feature extraction unit Fig. 2 from pre-selection unit reception result at this.
Fig. 8 is the structural drawing of an inspection unit, and operating personnel and integral unit can receive Output rusults from feature extraction unit simultaneously and provide result to the taxon Fig. 2 system.
Fig. 9 is the structural drawing of an inspection unit, and operating personnel and integral unit can receive Output rusults from taxon simultaneously and provide result to the output unit Fig. 2 system.
5. embodiment
Fig. 1 describes diagnosis algorithm can be lifted at the possibility noted abnormalities in digital X-ray photo, such as lung cancer bunch, the diagnosis of calcification and lump.
The view data of affected part skeleton view can be transmitted into picture input unit 15. for example, camera, CR (computer X-ray radiophotography x) system, DR (digital X-ray radiophotography x) system, FFDM system, or FILM digital quantizer can provide required data.Data in image input units 15 be saved for after retrieval and used or be transferred to graphics processing unit 35. at storer 25
Any suitable storer 25, comprises tape, compact disk, MO CD, light reservoir, external data center, or any other storer generally used.
Processing unit 35 be one can reading images and perform Different treatments to detect abnormal CAD unit.
The monitoring unit 56 of this invention can receive image from input block 15, processing unit 35 and storer 25 and send result to image input units 15, processing unit 35 and storer 25 and image output unit 45.
The principle that monitoring unit 55 and processing unit 35 are invented according to this.In principle, image can be exported to storage unit 25 be used for store and/or image output unit 45, such as screen, printer, draught machine, chart recorder, image communication machinery, etc. other similar products.
About Fig. 3, this theory structure schematic diagram indicates the processing unit 35 of CAD system robotization
About Fig. 2, this theory structure schematic diagram indicates processing unit 35. in the automated execution of CAD system and monitor mode when view data and obtains from mastography, and data can carry out multi-step (3505,3510 through image input process 3501,3515,3520,3525) process, comprising pre-service, preselected, feature extraction, classification, finally gives the abnormal lesion that result of detection indicates possibility.The automatically CAD system of this invention comprises five steps.Each step can generate intermediate result, is also CAD intermediate result.
The image that image input units 3501 can read must meet specific standard, such as DICOM, TIF or change into the specific format can be able to supported by current CAD system.Image input units 3501 only can be revised header and shows parameter and can not revise the view data comprising internal anatomy.This special case comprises the use mark the same with the view data 1 before or after image input units.
At second stage, digital X-ray photo 1 can carry out processing thus generating layered image with image segmentation by pretreatment unit 3505.Digital X-ray photo can be split according to or without mammary region.Can be removed without the pixel of mammary gland part in layergram, can not occur in processing procedure afterwards.Image enhancement technique can be used in here, utilizes different image difference to generate target enhance image, amplifies potential abnormal information thus.(highlighting potential exception thus)
At three phases, the pre-selection unit 3510 in doubtful lesion can use different search and matcher on the synergy picture of digital X-ray photo, extract the abnormal area image-region of possibility.
In fourth stage, feature extraction unit 3515 can use different calculation procedures different features to be extracted from the doubtful lesion image
At five-stage, in taxon 3520, employ different sorting algorithms, be used for the suspicious feature 450 of classifying respectively in each region; In different doubtful lesiones, generate probabilistic sorting algorithm according to different suspicious characteristic.
The exception be identified can be detected Output rusults 3525 and send. and result of detection exports 3525 can identify doubtful lesion (such as using circle to cover abnormal area); extremely can be instructed to equally (such as using arrow or hook), and the size of abnormal area (enclosing and 5 centimetres of circles as used 3 centimetres).The Output rusults 3525 of detecting device can also make testing result as a part for image.
Fig. 4 identifies this and invents the monitor mode of monitoring unit 55 and the schematic diagram of system that use, and the monitoring unit 55 of this invention simultaneously can carry out interaction with CAD unit 35.Monitoring unit 55 contains monitoring 1020, and this element combines monitoring and CAD intermediate result 1017 combines monitoring simultaneously and final CAD result 1012. monitoring unit 55 can receive original image 1, CAD intermediate result 505 and final CAD result 0105. from CAD unit 35
Monitoring unit 55 can receive view data from image input units 15 or storage element 25 equally.Monitoring 1020 can be doctors experience or other CAD detection systems being similar to unit 35.Monitor staff 1020 is for detecting original image 1, CAD intermediate result 505, or final CAD result 105 generate middle monitored results 1027 that these monitored results 1030 of monitored results 1030. can generate with CAD intermediate result understand returned to CAD unit 35.CAD unit 35 can continue CAD intermediate result 505 the process that starts.
The interaction of such CAD unit 35 and monitoring unit 55 can occur in arbitrary unit in any process in CAD unit and monitoring 55 and upper.Monitoring 55 can carry out interaction with the processing stage of CAD unit 33 plural.
After CAD unit 35 generates final CAD result 105, final CAD result 105 can be sent to monitoring unit 55 in order to further inspection.It is all get from monitoring CAD result 5 that monitor staff 1020 in monitoring unit 55 can check that original image 1 to generate in conjunction with result 1035. in conjunction with result 1035 and final CAD result 106 to the combining unit generating these monitored results 1030 of monitored results 1030. and final CAD result 105 and can be sent to monitored results and final CAD result 1012.Monitoring CAD result 5 can be delivered to radiologist 20 and monitor CAD result 5 comprise two classes to generate last diagnostic result 12.: (1.) final CAD result and (2.) monitoring unit 55 rely on final CAD result and original image 1 to generate in conjunction with result 1035
Fig. 5 illustrates mode and the system schematic that processing unit 35 in monitoring unit 55 assists monitoring 1020.Monitor staff 1020 reads original image 1 from image input units 3501 and CAD intermediate result 505 is sent back to the pretreatment unit 3505 of CAD unit 55 to generate the middle monitored results of middle monitored results 1027. by 1027.Other CAD processing unit (3505,3510,3520,3525) can be accurate from above process successively, as Fig. 3.
Fig. 6 processing unit 35 illustrated in this invention assists the monitored results in monitor staff 1020 and monitoring unit 55 in conjunction with the mode of CAD intermediate result 1017 and system schematic.
Monitor staff 1020 read from pretreatment unit 3505 original image 1 and CAD intermediate result 505 to generate monitor staff's result 1030. monitor staff 1020 can perform further image segmentation and or image enhaucament to generate monitored results 1030, this result can be revised breast area internal anatomy and be used for further process.Monitored results 1030 and CAD intermediate result can be fed to monitored results and CAD intermediate result combining unit 1017 is sent back to preselected 3510 of CAD unit 35 to generate the middle monitored results of middle monitored results 1027. 1027.Other CAD processing unit (3505,3510,3520,3525) can be accurate from above process successively, as Fig. 3.
Fig. 7 processing unit 35 illustrated in this invention monitoring unit 55 assists monitoring 1020 and monitored results and middle CAD in conjunction with the mode of result unit 1017 and system schematic.
Monitor staff 1020 reads original image 1 and CAD intermediate result 505 and determines whether increasing or reducing these suspicious regions to generate new a set of suspicious region, i.e. monitored results 1030 to the sum of the suspicious region generating monitored results 1030. monitor staff 1020 and can check indicated by pre-selection unit 3510 from pretreatment unit 3505.
Monitored results 1030 and CAD intermediate result can be fed to monitoring and CAD intermediate result combining unit 1017 is sent back to the feature extraction 3515 of CAD unit 35 to generate the middle monitored results 1027 of middle monitored results 1027..Other CAD processing unit (3505,3510,3520,3525) can be accurate from above process successively, as Fig. 3.
Fig. 8 processing unit 35 illustrated in this invention assists the monitored results in monitor staff 1020 and monitoring unit 55 from pretreatment unit 3505, to read original image 1 and CAD intermediate result 505 to the eigenwert generating monitored results 1030. monitor staff 1020 and can check that feature extraction unit 3515 extracts to revise these numerical value to generate new a set of characteristic parameter, i.e. monitored results 1030. in conjunction with the mode of CAD intermediate result 1017 and system schematic monitor staff 1020
Monitored results 1030 and CAD intermediate result can be fed to monitored results and CAD intermediate result combining unit 1017 can be sent back to the classification 3520 of CAD unit 35 to generate the middle monitored results 1027 of middle monitored results 1027..Other CAD processing unit (3505,3510,3520,3525) can be accurate from above process successively, as Fig. 3.
Fig. 9 processing unit 35 illustrated in this invention assists the monitored results in monitor staff 1020 and monitoring unit 55 from pretreatment unit 3505, to read original image 1 and CAD intermediate result 505 in conjunction with the mode of CAD intermediate result 1017 and system schematic monitor staff 1020 can read original image 1 and net result 105 to generate monitored results 1030. monitored results 1030 and final CAD result 105 can be fed to monitored results and final CAD result combining unit 1012 can be sent back to the detection 3525 output unit of CAD unit 35 to generate monitored results 5. monitored results 5 from taxon 3520 to generate monitored results 1030. monitor staff 1020.Other CAD processing unit (3505,3510,3520,3525) can be accurate from above process successively, as Fig. 3.
Monitored results 55 can two of CAD unit 33 processing stage. combining unit 1012 and 1017 can be operated in different algorithms, such as Bei Ensi algorithm and other similar fashion.
But should be understood that, method and system described herein can be modified within the scope of the invention.Such as, although above-listed described method and system is used to detection of lung cancer bunch, calcification and lump.But it should be understood that these method and systems can be used for detecting the cancer of other type equally as the Lung neoplasm in lung cancer, lump, cervical carcinoma, or the tumour at other positions at health.It also can be used for the detection of other form, and such as, at computed tomography (CT), magnetic resonance imaging (MRI) and ultrasonic middle detection are extremely.
Claims (10)
1. can detect an abnormal method in radiographs, such as lung cancer bunch, calcification and lump, the method comprises the following steps:
1.1 receive a series of X-ray photograph;
1.2 computer-aided diagnosis systems (CAD) can process a series of X-ray photograph to generate intermediate result and COMPUTER DETECTION Output rusults;
1.3 computer monitor detection output signals and intermediate result are all the results of computer detectable signal and the intermediate result revised, to be used for generating monitored results;
1.4 final detection result can be judged by radiologist.
2. claim 1, when a series of X-ray photograph of above-mentioned CAD process, can be processed by multiple method.
3. claim 2, above-mentioned plurality of step comprises image input step, pre-treatment step, preselected step, feature extraction step, and classifying step and testing result export step.
4. claim 3, above-mentioned pre-treatment step strengthens.
5. claim 3 also comprises, and above-mentioned preselected step have selected many places suspicious region to be used for next step process.
6. claim 3 also comprises, above-mentioned feature extraction step when processing further, for each suspicious region calculates characteristic parameter.
7. claim 3 also comprises, and above-mentioned classifying step can identify front and negative two kinds of discoveries exist.
8. claim 1 also comprises, and above-mentioned monitor and detection exports and intermediate result step comprises different computer process and artificial explanation.
9. claim 8 comprises, and above-mentioned artificial explanation employs a series of data thus generates objective testing result.
10. claim 8 also comprises, and the CAD mode of above-mentioned computer process is that one or more are different from the CAD mode used now.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105640577A (en) * | 2015-12-16 | 2016-06-08 | 深圳市智影医疗科技有限公司 | Method and system automatically detecting local lesion in radiographic image |
| CN109394250A (en) * | 2017-08-18 | 2019-03-01 | 柯尼卡美能达株式会社 | Image processing apparatus, image processing method and image processing program |
| CN110136806A (en) * | 2019-05-16 | 2019-08-16 | 南京绿旗喷墨技术有限公司 | A kind of medical imaging diagnostic printing system |
| CN110349669A (en) * | 2019-07-15 | 2019-10-18 | 杭州依图医疗技术有限公司 | Information display method, equipment and storage medium for image analysing computer |
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| CN105640577A (en) * | 2015-12-16 | 2016-06-08 | 深圳市智影医疗科技有限公司 | Method and system automatically detecting local lesion in radiographic image |
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Application publication date: 20150729 |