JP-7856098-B2 - Detection of the spine in image data

Inventors

• ヤーコビ アミール
• シルベルト オハッド
• エンヘルハルド ギー

Assignees

• コーニンクレッカ フィリップス エヌ ヴェ

Dates

Publication Date

20260511

Application Date

20211025

Priority Date

20201027

Claims (7)

1. A system configured to detect vertebrae of the spine in volumetric image data, comprising a computing device, wherein the computing device Vertebral detection module, A memory having instructions for the vertebral detection module, A processor configured to cause the vertebral detection module to execute the command to perform two-stage vertebral detection, wherein in the first stage of the two-stage vertebral detection, a first set of vertebral boundary boxes is detected in the sagittal image and clustered in the volumetric image data, and in the second stage of the two- stage vertebral detection , a panoramic image of the spine is generated based on the first set of detected boundary boxes, and a second set of vertebral boundary boxes is detected in the panoramic image, A display that shows a 2D image of a vertebra generated from a second set of vertebral boundary boxes , It has, The vertebra detection module detects the first set of vertebral bounding boxes based on a first predetermined minimum confidence threshold , and generates a 2D bounding box for the detected vertebra. The vertebral detection module combines the sagittal image and the 2D bounding box to generate a 3D model having a 3D bounding box. The vertebra detection module generates a curve that passes through the center of the 3D bounding box, The vertebral detection module samples lines from the 3D model along the projection of a vector from the anterior to the posterior part of the vertebrae at each point on the curve, onto a plane perpendicular to the curve at that point, thereby generating the panoramic image, which is a quasi-sagittal image including the entire vertebrae aligned vertically. The vertebra detection module detects the second set of vertebral bounding boxes based on a second predetermined minimum confidence threshold , and generates a 2D bounding box for the detected vertebra. The vertebra detection module converts the 2D bounding box of the panoramic image into a 3D space to define the 3D bounding box of the vertebrae. A system wherein the vertebra detection module has a YOLO-based neural network trained to detect vertebrae based on the minimum confidence threshold .
2. The system according to claim 1, wherein the detection of a first set of vertebral boundary boxes in the sagittal image by the vertebral detection module moves outward in both directions toward the first image and the last image of the sagittal image, starting from the central image of the sagittal image and until a stopping criterion is met .
3. The system according to claim 2 , wherein the stopping criterion includes the absence of detection of vertebrae in a predetermined number of consecutive images among the sagittal images.
4. The system according to any one of claims 1 to 3 , wherein the vertebra detection module labels each vertebra of the first set of boundary boxes as a sacrum, C2, or other vertebra.
5. The system according to any one of claims 1 to 4 , wherein the vertebral detection module extrapolates the curve to the anterior end of the first vertebra and the posterior end of the last vertebra to add the missing vertebra.
6. The system according to any one of claims 1 to 5 , wherein the vertebra detection module labels each vertebra of the second set of boundary boxes as a sacrum, C2, or other vertebra.
7. The system according to any one of claims 1 to 6 , wherein the computing device is an image storage and communication system (PACS).

Description

This invention generally relates to medical imaging informatics, and more particularly to the detection of the spine in image data. When a radiologist interprets an axial spinal image that has not been annotated by vertebral identification, it is difficult for the radiologist to determine which vertebra is represented in the axial spinal image without cross-referencing it with a sagittal spinal image and/or other images to determine the position of the axial spinal image relative to the spine. A schematic diagram illustrating an exemplary system according to embodiments of this specification, having a vertebral detection and labeling module configured to detect and label vertebrae of the spine in volumetric image data.This figure schematically shows an example of a vertebra detection and labeling module of the system shown in Figure 1, according to an embodiment of this specification.A schematic diagram illustrating an exemplary method for detecting and labeling vertebrae in volumetric image data according to embodiments of this specification. Figure 1 schematically shows an exemplary system 102 according to one embodiment of this specification. System 102 includes at least a data repository 104 and a computing device 106. The data repository 104 has a physical storage medium configured to store at least digital medical images. In one example, the data repository 104 is for a healthcare entity and includes digital medical images of a subject acquired by the healthcare entity's imaging modality. The physical storage medium is local to the healthcare entity and/or remote from the healthcare entity, such as a portion of a "cloud" based resource. Examples of imaging modalities include magnetic resonance imaging (MR), computed tomography (CT), single-photon emission tomography (SPECT), positron emission tomography (PET), and X-ray. The digital medical images include a series of two-dimensional (2D) images (collectively providing a three-dimensional (3D) volumetric image dataset) and/or a 3D volumetric image dataset. The digital medical images include at least images of the vertebrae of the subject's spine. The computing device 106 includes a processor 108 (e.g., a central processing unit (CPU), a microprocessor (CPU), a graphics processing unit (GPU), and/or other processors) and a computer-readable storage medium ("memory") 110 (excluding temporary media), such as a hard disk drive, a solid-state drive, or an optical disc. The memory 110 includes at least computer-executable instructions 112 and data 114. The processor 108 is configured to execute the computer-executable instructions 112. In one example, the computing system 106 is configured to provide storage, access, and/or processing of medical information, including digital medical images and electronic reports. An example of the computing device 106 includes, but is not limited to, an image storage and communication system (PACS). When the computing system 106 is a PACS, digital medical images and/or other electronic information are stored and/or transmitted via the DICOM (Digital Imaging and Communications in Medicine) format and/or another format. Instruction 112 includes at least instructions for the vertebra detection module 116. As will be described in more detail below, in one embodiment, the vertebra detection module 116 is configured to detect individual vertebrae in an image of the spine acquired in the sagittal plane ("sagittal image"), generate 2D bounding boxes for the detected vertebrae, combine the sagittal image and the 2D bounding boxes to generate a 3D model of the spine with a 3D bounding box, generate a panoramic image of the detected vertebrae based on the 3D model to generate a straight view of the spine, detect individual vertebrae in the panoramic image and generate 2D bounding boxes for the detected vertebrae in the panoramic image, convert the 2D bounding boxes into 3D space, and optionally annotate the displayed 2D image. As used herein, the bounding box borders or surrounds a vertebra with or without partial overlap of one or more adjacent vertebrae. In one example, the vertebra detection module 116 reduces the computational power required for detection and labeling 4 and/or improves the accuracy of vertebral visualization compared to a configuration without the vertebra detection module 116. Input devices 118, such as keyboards, mice, and touchscreens, communicate electrically with the computing system 102. In one example, the input devices 118 are configured to allow a user to operate the computing system 102 via user input, including activating the vertebral detection module 116 and selecting volumetric image data and/or sagittal images to load. Human-readable output devices 120, such as displays, also communicate electrically with the computing system 106. In one example, the output device 120 is configured to display 2D images of vertebrae, prompt the user for input, and present commands. Input/output ("I/O") 122 are config