US-20260127740-A1 - METHOD AND APPARATUS FOR GENERATING LESION MODEL OF TARGET SITE

Abstract

Disclosed are a method and apparatus for generating a lesion model of a tissue site, and a computer-readable storage medium. The method includes obtaining a determined lesion type of the tissue site, determining a plurality of determined sub-anatomical models from a model database of the tissue site based on the obtained determined lesion type, generating a lesion model of the tissue site based on the plurality of determined sub-anatomical models, and displaying the lesion model of the tissue site. Accordingly, the lesion model of the lesion type corresponding to the tissue site can be generated as disclosed herein.

Inventors

• Zixuan CHEN
• Muqing Lin
• Yaoxian Zou

Assignees

• SHENZHEN MINDRAY BIO-MEDICAL ELECTRONICS CO., LTD.

Dates

Publication Date

20260507

Application Date

20251230

Priority Date

20240407

Claims (20)

1. 1 . A method for generating a lesion model of a tissue site, comprising: providing a user interface, wherein the user interface comprises a control pointing to a lesion model generation mode; receiving an operation to the control on the user interface; and in response to the operation to the control on the user interface, entering a lesion model generation mode; wherein, in the lesion model generation mode: displaying a lesion type selection interface for the tissue site, wherein the lesion type selection interface comprises one or more lesion types; in response to an operation on the lesion type selection interface, determining a determined lesion type of the tissue site from the one or more lesion types in the lesion type selection interface; generating a lesion model of the tissue site based on the determined lesion type; and displaying the lesion model of the tissue site.
2. 2 . The method of claim 1 , wherein the generated lesion model comprises a plurality of sub-anatomical models, wherein at least two of the plurality of sub-anatomical models of the lesion model are located in different layers of the lesion model.
3. 3 . The method of claim 2 , further comprising: determining a sub-anatomical model desired to be highlighted in the displayed lesion model; and highlighting the determined sub-anatomical model.
4. 4 . The method of claim 1 , further comprising: editing the lesion model in response to an editing command to the displayed lesion model.
5. 5 . The method of claim 1 , wherein, the lesion model comprises a vascular model, and the method further comprises: determining a first position at the vascular model of the lesion model; according to the determined first position, adding a vascular branch model at the first position in the lesion model; or, determining a first position at the vascular model of the lesion model; determining a second position at the vascular model of the lesion model; and according to the determined first position and the determined second position, adding a bridging vascular model connecting the first position and the second position to the lesion model.
6. 6 . The method of claim 1 , wherein: the lesion model comprises a fetal heart model or a heart model, and the method further comprises: determining a position for defect in the fetal heart model or the heart model of the lesion model; and adding a ventricular septal defect model, an atrial septal defect model and/or an atrioventricular septal defect model at the position for defect in the lesion model.
7. 7 . The method of claim 1 , further comprising: determining a position for tumor in the lesion model; and adding a tumor model at the position for tumor in the lesion model.
8. 8 . The method of claim 1 , wherein: the lesion model comprises a vascular model, and the method further comprises: receiving a selection instruction for selecting a vascular model in the lesion model; determining a selected vascular model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position, an orientation, a diameter and/or a radius of the selected vascular model according to the adjustment instruction.
9. 9 . The method of a claim 1 , wherein: the lesion model comprises a defect model, and the method further comprises: receiving a selection instruction for selecting a defect model in the lesion model; determining a selected defect model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position and/or a size of the selected defect model according to the adjustment instruction.
10. 10 . The method of claim 1 , wherein: the lesion model comprises a tumor model, and the method further comprises: receiving a selection instruction for selecting a tumor model in the lesion model; determining a selected tumor model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position, a size and/or an orientation of the selected tumor model according to the adjustment instruction.
11. 11 . The method of claim 1 , wherein: the lesion model comprises an atrial model, a ventricular model or a myocardial model, and the method further comprises: receiving a selection instruction for selecting an atrial model, a ventricular model or a myocardial model in the lesion model; determining a selected atrial model, a selected ventricular model or a selected myocardial model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a size and/or a position of the selected atrial model or the selected ventricular model, or adjusting a position and/or a thickness of the selected myocardial model according to the adjustment instruction.
12. 12 . The method of claim 11 , further comprising: automatically adjusting a position and/or a size of a defect model associated with the selected atrial model, the selected ventricular model or the selected myocardial model according to the adjustment to the selected atrial model, the selected ventricular model or the selected myocardial model, such that the adjusted defect model matches the adjusted selected atrial model, the adjusted selected ventricular model or the adjusted selected myocardial model.
13. 13 . The method of claim 1 , wherein: the lesion model comprises an aortic valve model, and the method further comprises: receiving a selection instruction for selecting an aortic valve model in the lesion model; determining a selected aortic valve model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position and/or a size of the selected aortic valve model according to the adjustment instruction.
14. 14 . The method of claim 13 , further comprising: automatically adjusting a position and/or a size of a vascular model associated with the selected aortic valve model according to the adjustment to the selected aortic valve model, such that the adjusted vascular model matches the adjusted selected aortic valve model.
15. 15 . The method of claim 1 , wherein: the lesion model comprises a mitral valve model or a tricuspid valve model, and the method further comprises: receiving a selection instruction for selecting a mitral valve model or a tricuspid valve model in the lesion model; determining a selected mitral valve model or a selected tricuspid valve model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position, a size of opening and/or a valve thickness of the selected mitral valve model or the selected tricuspid valve model according to the adjustment instruction.
16. 16 . The method of claim 1 , further comprising: receiving a selection instruction for selecting a sub-anatomical model in the lesion model; determining a selected sub-anatomical model in the lesion model according to the received selection instruction; receiving an adjustment instruction; and adjusting a position, a shape, a size, an orientation and/or a thickness of the selected sub-anatomical model according to the adjustment instruction.
17. 17 . The method of claim 1 , wherein, in response to an operation on the lesion type selection interface, determining a determined lesion type of the tissue site from the one or more lesion types in the lesion type selection interface and generating a lesion model of the tissue site based on the determined lesion type comprising: receiving a first selection instruction for selecting a first determined lesion type on the lesion type selection interface; determining the first determined lesion type according to the received first selection instruction; determining a first lesion model according to the first determined lesion type; receiving a second selection instruction for selecting a second determined lesion type on the lesion type selection interface; determining the second determined lesion type according to the received second selection instruction; determining a second lesion model according to the second determined lesion type; and obtaining the lesion model of the tissue site according to the first lesion model and the second lesion model.
18. 18 . The method of claim 1 , further comprising: determining a position for new sub-anatomical model in the lesion model; and adding a new sub-anatomical model at the determined position for new sub-anatomical model.
19. 19 . An apparatus for generating a lesion model of a tissue site, comprising: a memory configured to store a program; and a processor configured to execute the program stored in the memory to: provide a user interface, wherein the user interface comprises a control pointing to a lesion model generation mode; receive an operation to the control on the user interface; and in response to the operation to the control on the user interface, enter a lesion model generation mode; wherein, in the lesion model generation mode: display a lesion type selection interface for the tissue site, wherein the lesion type selection interface comprises one or more lesion types; in response to an operation on the lesion type selection interface, determine a determined lesion type of the tissue site from the one or more lesion types in the lesion type selection interface; generate a lesion model of the tissue site based on the determined lesion type; and display the lesion model of the tissue site.
20. 20 . A computer-readable storage medium comprising a program, wherein the program is executable by a processor to: provide a user interface, wherein the user interface comprises a control pointing to a lesion model generation mode; receive an operation to the control on the user interface; and in response to the operation to the control on the user interface, enter a lesion model generation mode; wherein, in the lesion model generation mode: display a lesion type selection interface for the tissue site, wherein the lesion type selection interface comprises one or more lesion types; in response to an operation on the lesion type selection interface, determine a determined lesion type of the tissue site from the one or more lesion types in the lesion type selection interface; generate a lesion model of the tissue site based on the determined lesion type; and display the lesion model of the tissue site.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to Chinese Patent Application 202410410533.0, entitled “METHOD AND APPARATUS FOR GENERATING A LESION MODEL OF A TARGET SITE” filed with the China National Intellectual Property Administration on Apr. 7, 2024, all of which are incorporated herein by reference in their entirety. TECHNICAL FIELD The present disclosure relates to the field of medical engineering, in particular to methods and apparatus for generating a lesion model of a target site. BACKGROUND OF THE DISCLOSURE In real clinical practice, many patients exhibit complex diseases that do not conform to the simplified representations found in textbooks. These diseases often involve multiple lesions and exhibit diverse manifestations. A common example is congenital heart disease, which encompasses both single conditions and complex malformations, spanning a wide range of over a hundred specific subtypes and potentially including multiple malformations Multidisciplinary Team (MDT) consultations are recognized as the most effective way to treat complex diseases. However, due to the fact that medical reports are mostly descriptive text, the descriptions of complex diseases are obscure and difficult to comprehend, making it challenging for doctors to accurately depict the specific details of lesions or malformations in relation to clinical anatomy. In addition, patients frequently lack sufficient clinical knowledge and proper guidance, leading to anxiety and misunderstanding regarding complex diseases. These factors often contribute to ineffective MDT communication, potentially resulting in misdiagnosis. SUMMARY OF THE DISCLOSURE The present disclosure provides methods and apparatus for generating a lesion model of a tissue site, which will be specifically described below. In an embodiment, a method for generating a lesion model of a tissue site is provided, which may include: obtaining an ultrasound data of the tissue site;displaying a lesion type selection interface for the tissue site;determining a determined lesion type of the tissue site in response to an operation on the lesion type selection interface according to the ultrasound data;based on the determined lesion type of the tissue site, determining, from a model database of the tissue site, a plurality of determined sub-anatomical models corresponding to the determined lesion type;generating a lesion model of the tissue site based on the plurality of determined sub-anatomical models; anddisplaying the lesion model of the tissue site. In an embodiment, the model database of the tissue site may include a plurality of sub-anatomical models. The plurality of sub-anatomical models may include a category of general sub-anatomical model configured to define a complete anatomical structure of the tissue site. At least one of the category of general sub-anatomical model may include a plurality of general sub-anatomical models that are identical in category but different in morphology and are configured to distinguish lesion types of the tissue site. Alternatively, the plurality of sub-anatomical models may further include a category of special sub-anatomical model configured to distinguishing the lesion types of the tissue site. In an embodiment, the tissue site may include a fetal heart or a heart. The category of general sub-anatomical model may include a model of at least one of a chamber, a myocardial tissue, an arterial blood vessel, a valve and a venous blood vessel. The category of special sub-anatomical model may include a model of at least one of a defect, a foramen ovale and a tumor. In an embodiment, the tissue site may include a blood vessel. The category of general sub-anatomical model may include a model of at least one of a coronary artery, a carotid artery, an abdominal aorta and a superficial vein. The category of special sub-anatomical model may include a model of at least one of a plaque, and aneurysm and an embolism. In an embodiment, generating the lesion model of the tissue site based on the plurality of determined sub-anatomical models may include: superimposing the plurality of determined sub-anatomical models in a predetermined order to generate the lesion model. In an embodiment, the method in any one of the embodiments above may further include: in response to an edit command for the displayed lesion model, editing the lesion model. In an embodiment, said editing the lesion model may include at least one of: adding one or more sub-anatomical models to the lesion model;deleting one or more sub-anatomical models contained in the lesion model; andediting a morphology and/or a position of one or more sub-anatomical models contained in the lesion model. In an embodiment, the tissue site may include a fetal heart or a heart, and adding one or more sub-anatomical models to the lesion model may include at least one of: adding a vascular branch to the lesion model; adding a bridging vessel to the lesion model; addin