WO2022120869A1

WO2022120869A1 - Orientation identification method and device for intracerebral fragment electrode in craniocerebral medical image

Info

Publication number: WO2022120869A1
Application number: PCT/CN2020/136053
Authority: WO
Inventors: 唐建东
Original assignee: 苏州景昱医疗器械有限公司
Priority date: 2020-12-11
Filing date: 2020-12-14
Publication date: 2022-06-16
Also published as: CN112669938A; CN112669938B

Abstract

Disclosed in the present invention are an orientation identification method and device for an intracerebral fragment electrode in a craniocerebral medical image. The method comprises: first analyzing a craniocerebral medical image, obtaining the orientation coordinates of an intracerebral fragment electrode according to an analysis result, and according to the analysis result, establishing an individual craniocerebral model; calibrating the obtained orientation coordinates of the intracerebral fragment electrode on the individual craniocerebral model to form individualized intracerebral electrode positioning data; encoding the individualized intracerebral electrode positioning data to form an encoded data packet; and a mobile device directly displaying the orientation of the intracerebral fragment electrode on a display screen of the mobile device according to the encoded data packet. Further disclosed in the present invention is a device corresponding to the foregoing method. The present invention can intuitively display, on the mobile device, the spatial orientation of the intracerebral fragment electrode in a brain, and does not need a doctor to perform human determination according to an image, thereby improving the determination accuracy and shortening the human determination time, and also facilitating the implementation of remote inquiry.

Description

Method and equipment for orientation recognition of intracerebral sliced electrodes in cranial medical imaging

technical field

The invention relates to the technical field of medical imaging, in particular to a method and device for identifying the orientation of sliced electrodes in the brain in cranial medical imaging.

Background technique

In the medical industry, doctors usually use medical images to observe and diagnose the symptoms of patients. Brain medical images are an important basis for doctors to judge brain diseases. When doctors observe cranial medical images, they need to measure and analyze the EEG signal and locate the source of the EEG signal according to the spatial position of the sliced electrodes in the brain, so as to determine the location of the lesion. However, to judge the position and direction angle of the sliced electrodes in the brain, the patient must bring the image film when visiting the doctor. The doctor needs to directly compare the image film to judge the position of the electrode in the brain. This judgment needs to be based on the doctor's experience. The accuracy of judgment is low and time-consuming, and it is also inconvenient for remote consultation.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is to provide a method and device for recognizing the position of the sliced electrodes in the brain in cranial medical imaging, which can intuitively display the spatial orientation of the sliced electrodes in the brain on the mobile device, without the need for Doctors then make human judgments based on the images, which is conducive to improving the accuracy of judgments and shortening the time-consuming of judgments; it is also convenient for remote consultation.

In order to solve the above-mentioned technical problems, the technical solutions provided by the present invention are as follows:

A method for recognizing the position of an intracerebral sliced electrode in a cranial medical image, comprising the following steps:

1) Analyzing the cranial medical image, obtaining the orientation coordinates of the sliced electrodes in the brain according to the analysis results, and establishing an individual cranial brain model according to the analysis results;

2) calibrating the obtained azimuth coordinates of the sliced electrodes in the brain on the individual brain model to form individualized intracerebral electrode positioning data;

3) encoding the individualized intracerebral electrode positioning data to form an encoded data packet;

4) Send the encoded data packet to the mobile device, and the mobile device directly displays the orientation of the sliced electrodes in the brain on the display screen of the mobile device according to the encoded data packet.

In one embodiment, when analyzing the cranial medical image in step 1), the cranial medical image is first parsed into a DICOM format data file, and then the DICOM format data file is parsed, Thereby, the orientation coordinates of the sliced electrodes in the brain and the modeling data required for establishing the individual cranial model are obtained, and then the individual cranial model is established according to the modeling data obtained by analysis.

In one embodiment, after parsing the cranial medical image into a data file in DICOM format, it is also necessary to determine whether the data file in DICOM format has garbled characters. , until the parsing is successful, and then parse the successfully parsed data file in DICOM format to obtain the azimuth coordinates of the sliced electrodes in the brain and the modeling data needed to establish the individual brain model.

In one of the embodiments, a face rendering method is used in establishing the individual brain model.

In one of the embodiments, the volume rendering method is used in establishing the individual brain model.

In one of the embodiments, the volume rendering method adopts a ray casting algorithm, a stagger-deformation algorithm, a frequency domain volume rendering algorithm or a snowballing algorithm.

In one embodiment, the cranial medical image is a CT scan image, an MRI image, a radiological image or an ultrasound image.

In one embodiment, the mobile device includes a tablet computer or a mobile phone.

In one embodiment, the azimuth coordinates of the sliced electrodes in the brain include position coordinates and orientation angle coordinates of the sliced electrodes in the brain.

A device, comprising a memory, a processor and a computer program stored on the memory and running on the processor, when the processor executes the computer program, the intracerebral intracerebral medical imaging described in any one of the above is realized Orientation recognition method for segmented electrodes.

The present invention has the following beneficial effects: the method and device for recognizing the position of the intracerebral sliced electrodes in the cranial medical imaging of the present invention can enable the doctor to intuitively see the spatial position of the intracerebral sliced electrodes in the brain on the mobile device , which saves the time for doctors to analyze images and then make judgments when they visit a doctor, reduces the risk of misjudgment caused by human judgment; improves the accuracy of judgment; at the same time, it enables doctors to intuitively view on mobile devices at any time during remote video consultations. To the position of the slice electrode in the brain, it is more convenient to conduct remote consultation.

Description of drawings

1 is a structural block diagram of a method for recognizing the orientation of sliced electrodes in the brain in cranial medical imaging according to the present invention;

Detailed ways

The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

As shown in FIG. 1 , this embodiment discloses a method for recognizing the orientation of sliced electrodes in the brain in cranial medical imaging, including the following steps:

1) Analyze the cranial medical images, obtain the azimuth coordinates of the sliced electrodes in the brain according to the analysis results, and establish an individual brain model (3D model) according to the analysis results;

3) Encoding and processing the individualized intracerebral electrode positioning data to form an encoded data packet, so as to encode a data format that can be displayed on a mobile device;

4) Send the encoded data packet to the mobile device, and the mobile device directly displays the three-dimensional spatial orientation of the segmented electrodes in the brain on the display screen of the mobile device according to the encoded data packet.

In one embodiment, when the cranial medical image is parsed in step 1), the cranial medical image is first parsed into a data file in DICOM format, and then the data file in DICOM format is parsed to obtain intracerebral slices The orientation coordinates of the electrodes and the modeling data required to establish the individual brain model are obtained, and then the individual brain model is established according to the modeling data obtained through analysis.

Among them, DICOM (Digital Imaging and Communications in Medicine) is medical digital imaging and communication, which is an international standard for medical images and related information (ISO 12052); it defines a medical image format that can meet clinical needs and can be used for data exchange.

The data file in DICOM format consists of a 128-byte preamble (Premble), a four-byte prefix (Prefix) and a data element (DataElement). The preamble is the description of the file information; the byte prefix is the identification of the DICOM file; the data element Arrange in order, and arrange them to the end of the file in the form of one data element by one data element; the various data we want to read in the DICOM file is in each data element;

Each data element is divided into 4 fields, namely tag field, value description field, value length field and value field. Among them, the tag field (Tag) has a total of 4 bytes, the first 2 bytes are the group number, and the last 2 bytes is the element number; the Value Representation (VR) field is 2 bytes, specifying the type format of the data element; the Value Length field (VL) is 2 or 4 bytes in total, which is an unsigned integer, and the value length field The value of must be an even number; Value Field (VF) reads the data value of the corresponding value length field according to the format of the value description field.

In one of the embodiments, the face rendering method is used to build the individual brain model.

The surface rendering algorithm performs 3D modeling based on the method of constructing the surface of the object. It regards a series of 2D slice data as a 3D data field, and constructs the surface mesh of the 3D model by extracting the isosurface of the 3D data. Then a 3D model is constructed.

When using the surface rendering method to build an individual brain model, the DICOM format data file is analyzed to extract structures such as epidermis and bones, and then three-dimensional rendering is performed on the extracted surface using triangular surfaces.

The method for establishing an individual brain model using the face rendering method specifically includes the following steps:

A1) Parse the data file in DICOM format, extract the pixel resolution in the three directions of X, Y, and Z axes, and combine the layer number and grayscale image data in the Z axis direction into data in RAW-DATA format;

A2) Reconstruct the two-dimensional image according to the data in RAW-DATA format;

A3) along the Z-axis direction, map the image of each layer into a two-dimensional texture, and use the gray value as the RGBA value of the texture;

A4) Along the Z-axis, draw the image of each layer, and use the two-dimensional image texture of the corresponding layer to map, so as to form a three-dimensional individual brain model.

In one of the embodiments, the volume rendering method can also be used when establishing the individual brain model. The volume rendering algorithm performs three-dimensional modeling based on directly drawing three-dimensional voxels of objects, that is, by directly drawing each pixel of the three-dimensional data, a three-dimensional three-dimensional model containing internal spatial information is constructed.

Further, the volume rendering method adopts a ray-casting algorithm (Ray-casting), a shear-warp algorithm (Shear-warp), a frequency domain volume rendering algorithm (Frequency Domain) or a snowball-throwing algorithm (Splatting).

In one embodiment, the cranial medical image is a CT scan image, a magnetic resonance imaging (MRI), a radiological image, or an ultrasound image (an image formed using ultrasound imaging technology).

In one embodiment, the mobile device includes a tablet or a cell phone.

In one embodiment, the orientation coordinates of the sliced electrodes in the brain include position coordinates and orientation angle coordinates of the sliced electrodes in the brain.

This embodiment also discloses a device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the brain of any of the above-mentioned embodiments is implemented. A method for orientation recognition of sliced electrodes in the brain in medical imaging.

This embodiment also discloses a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, realizes the orientation recognition of the sliced electrodes in the brain in the cranial medical image described in any of the above embodiments method.

The method for recognizing the orientation of the sliced electrodes in the brain in this embodiment can automatically identify the orientation coordinates of the sliced electrodes in the brain, and calibrate the orientation coordinates of the sliced electrodes in the brain on the individual cranial model to form an individual After analyzing the intracerebral electrode positioning data, the individualized intracerebral electrode localization data is finally programmed into a data packet format that can be displayed directly on the mobile device, so that the doctor can intuitively see the position of the intracerebral sliced electrodes on the mobile device. , the doctor does not need to compare the images to make artificial judgments, saves the time for doctors to analyze the images and then makes judgments when they visit a doctor, reduces the risk of misjudgment caused by human judgments; improves the accuracy of judgments, and saves time for manual judgments; It is no longer necessary to carry the imaging film with you when visiting a doctor, which brings convenience to the patient, and also enables the doctor to intuitively see the position of the sliced electrodes in the brain on the mobile device at any time during the remote video consultation, which is more convenient for remote consultation. conduct of the consultation.

From the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be realized by software and necessary general-purpose hardware, and of course can also be realized by hardware, but in many cases the former is a better embodiment . Based on such understanding, the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products can be stored in a computer-readable storage medium, such as a floppy disk of a computer , read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including several instructions to make a computer device (which can be a personal computer , server, or network device, etc.) to execute the method for recognizing the position of the sliced electrodes in the brain in the cranial medical imaging according to the various embodiments of the present invention.

The above-mentioned embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art on the basis of the present invention are all within the protection scope of the present invention. The protection scope of the present invention is subject to the claims.

Claims

A method for recognizing the position of sliced electrodes in the brain in craniocerebral medical images, which is characterized by comprising the following steps:

1) Analyzing the cranial medical image, obtaining the orientation coordinates of the sliced electrodes in the brain according to the analysis results, and establishing an individual cranial brain model according to the analysis results;

2) calibrating the obtained azimuth coordinates of the sliced electrodes in the brain on the individual brain model to form individualized intracerebral electrode positioning data;

3) encoding the individualized intracerebral electrode positioning data to form an encoded data packet;

4) Send the encoded data packet to the mobile device, and the mobile device directly displays the orientation of the sliced electrodes in the brain on the display screen of the mobile device according to the encoded data packet.
The method for recognizing the position of the intracerebral sliced electrodes in the cranial medical image according to claim 1, characterized in that, when analyzing the cranial medical image in the step 1), the cranial medical image is first The image is parsed into a DICOM format data file, and then the DICOM format data file is parsed to obtain the azimuth coordinates of the sliced electrodes in the brain and the modeling data required to establish an individual cranial model, and then analyze the obtained modeling data. Data to build individual brain models.
The method for recognizing the orientation of sliced electrodes in the brain in cranial medical images according to claim 2, wherein after parsing the cranial medical images into data files in DICOM format, it is also necessary to determine the data files in DICOM format. Whether there is garbled characters, if it is judged to be no, it is judged that the parsing is successful, otherwise, the parsing is performed again until the parsing is successful, and then parsing the successfully parsed DICOM format data file to obtain the azimuth coordinates of the sliced electrodes in the brain and obtain the Modeling data needed to build individual brain models.
The method for recognizing the position of sliced electrodes in the brain in craniocerebral medical images according to claim 2, characterized in that a face drawing method is used when establishing the individual cranial model.
The method for recognizing the orientation of sliced electrodes in the brain in cranial medical images according to claim 2, wherein a volume rendering method is used when establishing the individual cranial model.
The method for recognizing the orientation of sliced electrodes in craniocerebral medical images according to claim 5, wherein the volume rendering method adopts a ray casting algorithm, a stagger-deformation algorithm, a frequency domain volume rendering algorithm or a snow throwing algorithm. ball algorithm.
The method for recognizing the position of sliced electrodes in the brain in a cranial medical image according to claim 1, wherein the cranial medical image is a CT scan image, a nuclear magnetic resonance image, a radiological image or an ultrasound image.
The method for recognizing the position of sliced electrodes in the brain in cranial medical images according to claim 1, wherein the mobile device comprises a tablet computer or a mobile phone.
The method for recognizing the orientation of the intracerebral sliced electrodes in craniocerebral medical imaging according to claim 1, wherein the orientation coordinates of the intracerebral sliced electrodes include position coordinates and direction angle coordinates of the intracerebral sliced electrodes.
A device, comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor implements any one of claims 1-9 when executing the computer program The method for recognizing the position of the sliced electrodes in the brain in the craniocerebral medical image.