Automated quality assessment of ultra-widefield angiography images

A system for fully automated quality assessment of ultra-widefield angiography images, the system comprising:

• a processor;
• and
• a non-transitory computer readable medium storing instructions executable by the processor, the machine executable instructions comprising:
• an image interface that receives a series of ultra-widefield angiography images of a retina of a patient;
• a neural network, trained on a set of labeled images, that generates a quality parameter for each of the series of ultra-widefield angiography images representing a quality of the image, each of the set of labeled images being assigned to one of a plurality of classes representing image quality;
• and
• a user interface that provides an instruction to a user to obtain a new series of ultra-widefield angiography images of the retina of the patient if no image of the series of ultra-widefield angiography images has a quality parameter that meets a threshold value.

A system for fully automated quality assessment of ultra-widefield angiography images, the system comprising:

• an ultra-widefield angiography imaging system;
• a processor;
• and
• a non-transitory computer readable medium storing instructions executable by the processor, the machine executable instructions comprising:
• an image interface that receives a series of ultra-widefield angiography images of a retina of a patient from the ultra-widefield angiography imaging system;
• a neural network, trained on a set of labeled images, that generates a quality parameter for each of the series of ultra-widefield angiography images representing a quality of the image, each of the set of labeled images being assigned to one of a plurality of classes representing image quality;
• a user interface that provides an instruction to a user to obtain a new series of ultra-widefield angiography images of the retina of the patient if the no image of the series of ultra-widefield angiography images has a quality parameter that meets a threshold value;
• and
• an image selector that selects a proper subset of the series of ultra-widefield angiography images according to the quality parameter generated for each image at the neural network.