System and method for identifying feature in an image of a subject
A method and system is disclosed for analyzing image data of a subject. The image data can be collected with an imaging system in a selected manner and/or motion. The image data may include selected overlap and be acquired with an imaging system that generates a plurality of perspectives for more than one location. An automatic system and method may then define or identify various features and/or allow for registration for alternative image data.
1 . A method of detecting and classifying a feature in an image based on a plurality of individual image projections generated with an imaging system, the method comprising:
acquiring the plurality of individual image projections, the plurality of individual image projections comprising:
a first set of individual image projections from a first view of a subject, and
a second set of individual image projections from a second view of the subject,
wherein the first view is different than the second view;
determining proposed regions for the feature in each of a first feature map and a second feature map, wherein the first feature map is associated with the first view and the second feature map is associated with the second view;
combining the proposed regions of the feature in each of the first feature map and the second feature map;
classifying the feature and determining a position of the feature in each of the first view and the second view based on combining the proposed regions; and
outputting the determination of the position of the feature in each of a first output view and a second output view, wherein:
the first output view includes a first label identifying the feature and the position of the feature in the first output view, and
the second output view includes a second label identifying the feature and the position of the feature in the second output view.
2 . The method of claim 1 , wherein the determination of the proposed regions is based on a machine learning algorithm operable to recognize the feature in the plurality of individual image projections.
3 . The method of claim 1 , wherein the first view is a lateral view and the second view is an anterior-to-posterior view.
4 . The method of claim 1 , wherein the first view is an anterior-to-posterior view and the second view is different than the anterior-to-posterior view.
5 . The method of claim 1 , wherein the feature is extracted in each of the first view and the second view.
6 . The method of claim 5 , further comprising:
determining region proposals for the feature in each of the first view and the second view; and
aligning the region proposals between the first view and the second view.
7 . The method of claim 6 , wherein combining the proposed regions of the feature in each of the first feature map and the second feature map comprises:
concatenating the aligned region proposals of the first view and the second view.
8 . The method of claim 7 , further comprising:
evaluating the concatenated aligned region proposals via a region proposal convolutional neural network, wherein determining the position of the feature is based on evaluating the concatenated aligned region proposals.
9 . The method of claim 8 , further comprising:
confirming the classification of the feature based at least in part on imposing an order on classification of a plurality of features.
10 . The method of claim 1 ,
wherein the plurality of individual image projections are acquired with a slot filter;
wherein acquiring the plurality of individual image projections includes acquiring a set of individual slot image projections of the subject with an imaging head at a selected position relative to the subject;
wherein the slot filter includes a plurality of slots configured to cause the generation of the set of individual slot image projections simultaneously; and
wherein each individual slot image projection of the set of individual slot image projections has a unique perspective of the subject relative to each other individual slot image projection; wherein the first view and the second view are both generated with a selected set of the plurality of individual image projections.
11 . The method of claim 1 , wherein the plurality of individual image projections are generated via an x-ray source configured to emit a beam of x-rays.
12 . A system to detect and classify a feature in an image based on a plurality of individual image projections generated with an imaging system, the system comprising:
a processor module configured to execute instructions to:
acquire the plurality of individual image projections, the plurality of individual image projections comprising:
a first set of individual image projections from a first view of a subject, and
a second set of individual image projections from a second view of the subject, wherein the first view is different than the second view;
determine proposed regions for the feature in each of a first feature map and a second feature map, wherein the first feature map is associated with the first view and the second feature map is associated with the second view;
combine the proposed regions of the feature in each of the first feature map and the second feature map;
classify the feature and determining a position of the feature in each of the first view and the second view based on combining the proposed regions; and
output the determination of the position of the feature in each of a first output view and a second output view, wherein:
the first output view includes a first label identifying the feature and the position of the feature in the first output view, and
the second output view includes a second label identifying the feature and the position of the feature in the second output view.
13 . The system of claim 12 , wherein the determination of the proposed regions is based on a machine learning algorithm operable to recognize the feature in the plurality of individual image projections.
14 . The system of claim 12 , wherein the acquired first view is a lateral view and the acquired second view is an anterior-to-posterior view.
15 . The system of claim 12 , wherein the feature is extracted in each of the acquired first view and the acquired second view.
16 . The system of claim 15 , wherein the processor module is further configured to execute instructions to:
determine region proposals for the feature in each of the first view and the second view; and
align the region proposals between the first view and the second view.
17 . The system of claim 16 , wherein, to combine the proposed regions of the feature in each of the first feature map and the second feature map, the processor module is configured to execute instructions to:
concatenate the aligned region proposals of the first view and the second view.
18 . The system of claim 17 , wherein the processor module is further configured to execute instructions to:
evaluate the concatenated aligned region proposals via a region proposal convolutional neural network, wherein determination of the position of the feature is based on evaluation of the concatenated aligned region proposals.
19 . The system of claim 18 , wherein the processor module is further configured to execute instructions to:
confirm the classification of the feature based at least in part on imposing an order on classification of a plurality of features.
20 . The system of claim 12 ,
wherein, to acquire the plurality of individual image projections, the processor module is configured to execute instructions to acquire the plurality of individual image projections with a slot filter;
wherein, to acquire the plurality of individual image projections, the processor module is configured to execute instructions to acquire a set of individual slot image projections of the subject with an imaging head at a selected position relative to the subject;
wherein the slot filter includes a plurality of slots configured to cause the generation of the set of individual slot image projections simultaneously; and
wherein each individual slot image projection of the set of individual slot image projections has a unique perspective of the subject relative to each other individual slot image projection.
21 . The system of claim 12 , further comprising:
an x-ray source configured to emit a beam of x-rays;
a slot filter configured to split the beam of x-rays into at least two slot beams of x-rays; and
a detector configured to detect the slot beams of x-rays.
22 . The system of claim 12 , wherein the first view is an anterior-to-posterior view and the second view is different than the anterior-to-posterior view.