Systems, devices, and methods for generating data series to visualize quantitative structure data registered to imaging data

A method for processing image data of patient anatomy, the method comprising:

• imaging, with an imaging device, anatomical structures of a patient;
• generating, with the imaging device, anatomical image data corresponding to the anatomical structures;
• and
• performing, with a compute device, anatomical analysis of the anatomical image data received from the imaging device, the anatomical analysis comprising:
• providing, to a segmentation analysis model, the anatomical image data, wherein the segmentation analysis model comprises a segmentation convolutional neural network (CNN) model, wherein the segmentation analysis model is selected based on a type of the imaging device;
• receiving, from the segmentation analysis model, segmentation of the anatomical image data identifying one or more anatomical parts of interest of the anatomical structures;
• providing, to a level identification model, the anatomical image data, wherein the level identification model comprises a level identification CNN model;
• receiving, from the level identification model, a set of levels for different regions of a spine of the patient;
• identifying one or more anatomical features within the anatomical image data based on the one or more anatomical parts of interest and the set of levels for different regions;
• providing, to a spinal analysis model, the anatomical image data, wherein the spinal analysis model comprises a neural network model;
• and
• receiving, from the spinal analysis model, a classification of one or more anatomical structures captured in the anatomical image data, wherein the classification comprises an indication of a spinal condition or deformity.

A method for processing image data of patient anatomy, the method comprising:

• imaging, with an imaging device, anatomical structures of a patient;
• generating, with the imaging device, anatomical image data corresponding to the anatomical structures;
• and
• performing, with a compute device, anatomical analysis of the anatomical image data received from the imaging device, the anatomical analysis comprising:
• providing, to a segmentation analysis model, the anatomical image data, wherein the segmentation analysis model comprises a segmentation convolutional neural network (CNN) model;
• receiving, from the segmentation analysis model, segmentation of the anatomical image data identifying one or more anatomical parts of interest of the anatomical structures;
• providing, to a level identification model, the anatomical image data, wherein the level identification model comprises a level identification CNN model, wherein the level identification model is selected based on a type of the imaging device;
• receiving, from the level identification model, a set of levels for different regions of a spine of the patient;
• identifying one or more anatomical features within the anatomical image data based on the one or more anatomical parts of interest and the set of levels for different regions;
• providing, to a spinal analysis model, the anatomical image data, wherein the spinal analysis model comprises a neural network model;
• and
• receiving, from the spinal analysis model, a classification of one or more anatomical structures captured in the anatomical image data, wherein the classification comprises an indication of a spinal condition or deformity.