CN102525660A - Operation navigation instrument with function of automatically recognizing lesion at craniocerebral part - Google Patents
Operation navigation instrument with function of automatically recognizing lesion at craniocerebral part Download PDFInfo
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- CN102525660A CN102525660A CN2012100358972A CN201210035897A CN102525660A CN 102525660 A CN102525660 A CN 102525660A CN 2012100358972 A CN2012100358972 A CN 2012100358972A CN 201210035897 A CN201210035897 A CN 201210035897A CN 102525660 A CN102525660 A CN 102525660A
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Abstract
The invention discloses an operation navigation instrument with the function of automatically recognizing a lesion at a craniocerebral part. The operation navigation instrument comprises a data reading module for reading image data of the craniocerebral part, wherein the data reading module is connected with an identifying module used for identifying the lesion in the image data of each layer, and the identifying module is connected with a modeling module used for establishing a craniocerebral part structure and lesion three-dimensional model by using a three-dimensional rebuilding manner. The operation navigation instrument disclosed by the invention can be used for intelligently recognizing brain tumors and other lesion parts to effectively increase the efficiency and safety of an operation.
Description
Technical field
The present invention relates to a kind of Medical Instruments.
Background technology
All operation navigation devices all can only be manual read's sheets now, manual delimitation focus zone, and inefficiency, manual operation is inconvenient, and mistake is drawn the rate height.
Summary of the invention
The object of the present invention is to provide a kind of can intelligent identification brain tumor etc. lesions position, improve the efficient of operation and the surgical navigational appearance with the automatic recognition function of cranium brain lesion of safety.
Technical solution of the present invention is:
A kind of surgical navigational appearance with the automatic recognition function of cranium brain lesion; It is characterized in that: comprise the data read module that reads cranium brain image data; Data read module is connected with the identification module that the focus in every layer the graph data is identified, and identification module is connected with the MBM that uses the three-dimensional reconstruction mode to set up a cranium all brain structures and focus threedimensional model; Wherein read module is based on anatomical priori and statistical analysis; According to the seriality of the same tissue of human body and the intermittence between the Different Organs; The structure anatomical atlas carries out registration with normal brain template and pathological changes image, and the identification lesions position is abnormal area roughly; Adopt continuous prediction from coarse to fine then, rolling optimization; Identification module identifies peculiar focus through focus data and normal organ data contrast; MBM reads in brainpan data and lesions position data, carries out three-dimensional reconstruction.
Said identification module is through focus data and normal organ data contrast; The concrete grammar that identifies peculiar focus is: to each candidate focal zone, calculate its characteristic, obtain area, size, gray scale mean square deviation parameter; Contrast the information in the clinical focus characteristic storehouse that obtains again; Judge the doubtful degree of focal zone, and be followed successively by the doubtful degree of each doubtful zone definitions, confirm the focus zone through man-machine interaction mode at last.
Said MBM reads in brainpan data and lesions position data; The concrete grammar that carries out three-dimensional reconstruction is: read cranium brain data and focal zone data; Adopt sophisticated volume drawing business software to set up the stereoscopic three-dimensional model of cranium brain data, and adopt sophisticated iso-surface patch business software to set up the threedimensional model of focal zone, then above-mentioned two models are read in a display unit; Realizing mixed display, is the selected various colors of two models by user again.
The present invention can intelligently discern lesions positions such as brain tumor, effectively improves the efficient and the safety of operation.
Description of drawings
Below in conjunction with accompanying drawing and embodiment the present invention is described further.
Fig. 1 is the operation principle block diagram of read module.
Fig. 2 is the operation principle block diagram of identification module.
Fig. 3 is the operation principle block diagram of MBM.
The specific embodiment
A kind of surgical navigational appearance with the automatic recognition function of cranium brain lesion; The data read module that comprises the cranium brain image data that reads MR and CT; Data read module is connected with the identification module that the focus in every layer the graph data is identified, and identification module is connected with the MBM that uses the three-dimensional reconstruction mode to set up a cranium all brain structures and focus threedimensional model; Wherein read module is based on anatomical priori and statistical analysis; According to the seriality of the same tissue of human body and the intermittence between the Different Organs; The structure anatomical atlas carries out registration with normal brain template and pathological changes image, and the identification lesions position is abnormal area roughly; Adopt continuous prediction from coarse to fine then, rolling optimization; Identification module identifies peculiar focus through focus data and normal organ data contrast; MBM reads in brainpan data and lesions position data, carries out three-dimensional reconstruction.
Said identification module is through focus data and normal organ data contrast; The concrete grammar that identifies peculiar focus is: to each candidate focal zone, calculate its characteristic, obtain area, size, gray scale mean square deviation parameter; Contrast the information in the clinical focus characteristic storehouse that obtains again; Judge the doubtful degree of focal zone, and be followed successively by the doubtful degree of each doubtful zone definitions, confirm the focus zone through man-machine interaction mode at last.
Said MBM reads in brainpan data and lesions position data; The concrete grammar that carries out three-dimensional reconstruction is: read cranium brain data and focal zone data; Adopt sophisticated volume drawing business software to set up the stereoscopic three-dimensional model of cranium brain data, and adopt sophisticated iso-surface patch business software to set up the threedimensional model of focal zone, then above-mentioned two models are read in a display unit; Realizing mixed display, is the selected various colors of two models by user again.
Claims (3)
1. surgical navigational appearance with the automatic recognition function of cranium brain lesion; It is characterized in that: comprise the data read module that reads cranium brain image data; Data read module is connected with the identification module that the focus in every layer the graph data is identified, and identification module is connected with the MBM that uses the three-dimensional reconstruction mode to set up a cranium all brain structures and focus threedimensional model; Wherein read module is based on anatomical priori and statistical analysis; According to the seriality of the same tissue of human body and the intermittence between the Different Organs; The structure anatomical atlas carries out registration with normal brain template and pathological changes image, and the identification lesions position is abnormal area roughly; Adopt continuous prediction from coarse to fine then, rolling optimization; Identification module identifies peculiar focus through focus data and normal organ data contrast; MBM reads in brainpan data and lesions position data, carries out three-dimensional reconstruction.
2. the surgical navigational appearance with the automatic recognition function of cranium brain lesion according to claim 1; It is characterized in that: said identification module is through focus data and normal organ data contrast; The concrete grammar that identifies peculiar focus is: to each candidate focal zone, calculate its characteristic, obtain area, size, gray scale mean square deviation parameter; Contrast the information in the clinical focus characteristic storehouse that obtains again; Judge the doubtful degree of focal zone, and be followed successively by the doubtful degree of each doubtful zone definitions, confirm the focus zone through man-machine interaction mode at last.
3. the surgical navigational appearance with the automatic recognition function of cranium brain lesion according to claim 1 and 2; It is characterized in that: said MBM reads in brainpan data and lesions position data; The concrete grammar that carries out three-dimensional reconstruction is: read cranium brain data and focal zone data; Adopt sophisticated volume drawing business software to set up the stereoscopic three-dimensional model of cranium brain data, and adopt sophisticated iso-surface patch business software to set up the threedimensional model of focal zone, then above-mentioned two models are read in a display unit; Realizing mixed display, is the selected various colors of two models by user again.
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| CN201210035897.2A CN102525660B (en) | 2012-02-17 | 2012-02-17 | Operation navigation instrument with function of automatically recognizing lesion at craniocerebral part |
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| CN201210035897.2A CN102525660B (en) | 2012-02-17 | 2012-02-17 | Operation navigation instrument with function of automatically recognizing lesion at craniocerebral part |
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| CN102525660A true CN102525660A (en) | 2012-07-04 |
| CN102525660B CN102525660B (en) | 2014-02-05 |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106326856A (en) * | 2016-08-18 | 2017-01-11 | 厚凯（天津）医疗科技有限公司 | Surgery image processing method and surgery image processing device |
| CN108261241A (en) * | 2018-01-16 | 2018-07-10 | 河北瑞鹤医疗器械有限公司 | Orthopedic implant method for customizing, apparatus and system |
| CN110738701A (en) * | 2019-10-23 | 2020-01-31 | 左丙丽 | tumor three-dimensional positioning system |
| CN110974415A (en) * | 2019-12-19 | 2020-04-10 | 向欣 | Method for establishing three-dimensional contrast aneurysm form database of aneurysm volume |
| CN111583219A (en) * | 2020-04-30 | 2020-08-25 | 赤峰学院附属医院 | Analysis method and device for craniomaxillofacial soft and hard tissues and electronic equipment |
| CN113768619A (en) * | 2020-06-10 | 2021-12-10 | 长庚大学 | Path positioning method, information display device, storage medium and integrated circuit chip |
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| CN106326856A (en) * | 2016-08-18 | 2017-01-11 | 厚凯（天津）医疗科技有限公司 | Surgery image processing method and surgery image processing device |
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| CN113768619A (en) * | 2020-06-10 | 2021-12-10 | 长庚大学 | Path positioning method, information display device, storage medium and integrated circuit chip |
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| US11806088B2 (en) | 2020-06-10 | 2023-11-07 | Chang Gung University | Method, system, computer program product and application-specific integrated circuit for guiding surgical instrument |
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| CN102525660B (en) | 2014-02-05 |
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Address after: Yongtong Road on the eastern side of Rudong County Economic Development Zone 226400 Jiangsu city of Nantong Province Patentee after: Jiangsu love medical Polytron Technologies Inc Address before: 226401 Jiangsu city of Nantong province Rudong County town of Jianshe Road Matang No. 4 Patentee before: Nantong Apon Medical Appliance Co., Ltd. |