Systems and methods for segmenting medical images based on anatomical landmark-based features

A computer-implemented method for segmenting medical images, the method comprising:

• receiving an image acquired by an imaging device;
• identifying a plurality of landmark points within the image, each landmark point corresponding to a known anatomical landmark;
• selecting an image point in the image;
• determining, by a processor, at least one feature for the image point relative to the plurality of landmark points;
• and
• associating, by the processor, the image point with an anatomical structure by using a classification model based on the at least one determined feature.

A computer-implemented method for training a classification model used for segmenting medical images acquired by an imaging device, the method comprising:

• receiving a training image, the training image including a plurality of image points, each image point being assigned an anatomical structure;
• identifying a plurality of landmark points in the training image, each landmark point corresponding to a known anatomical landmark;
• determining one or more features for each image point in the training image relative to the landmark points;
• and
• using the plurality of image points as training data to train the classification model, wherein the classification model associates an unclassified image point with an anatomical structure based on the one or more determined features for the unclassified image point.

A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a computer, cause the computer to perform a method for segmenting medical images, the method comprising:

• receiving an image acquired by an imaging device;
• identifying a plurality of landmark points within the image, each landmark point corresponding to a known anatomical landmark;
• selecting an image point in the image;
• determining at least one feature for the image point relative to the plurality of landmark points;
• and
• associating the image point with an anatomical structure by using a classification model based on the at least one determined feature.

A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a computer, cause the computer to perform a method for training a classification model used for segmenting medical images acquired by an imaging device, the method including:

• receiving a training image, the training image including a plurality of image points, each image point being assigned an anatomical structure;
• identifying a plurality of landmark points in the training image, each landmark point corresponding to a known anatomical landmark;
• determining one or more features for each image point in the training image relative to the landmark points;
• and
• using the plurality of image points as training data to train the classification model, wherein the classification model associates an unclassified image point with an anatomical structure based on the one or more determined features for the unclassified image point.

A system for segmenting medical images acquired by an imaging device using a classification model, the system comprising:

• a database configured to store a plurality of images acquired by the imaging device;
• and
• an image processor connected to the database to access the plurality of images, image processor configure to:
• receive an image from the database;
• identify a plurality of landmark points within the image, each landmark point corresponding to a known anatomical landmark;
• select an image point in the image;
• determine at least one feature for the image point relative to the plurality of landmark points;
• and
• associate the image point with an anatomical structure by using the classification model, based on the at least one determined feature.

A system for training a classification model used for segmenting medical images acquired by an imaging device, the system comprising:

• a database configured store a plurality of training images, each training image including a plurality of image points and each image point is assigned an anatomical structure;
• and
• an image processor connected to the database to access the plurality of training images, the image processor configured to:
• receive a training image from the database, the training image including a plurality of image points and each image point within the training image being assigned an anatomical structure;
• identify a plurality of landmark points in the training image, each landmark point corresponding to a known anatomical landmark;
• determine one or more features for each image point in the training image relative to the plurality of landmark points;
• and
• use the plurality of image points as training data to train the classification model, wherein the classification model associates an unclassified image point with an anatomical structure based on the one or more determined features for the unclassified image point.