Large vessel occlusion detection and classification in medical imaging

An apparatus comprising:

• means for receiving an input medical image of one or more vessels in an anatomical object of a patient;
• means for identifying one or more anatomical landmarks in the input medical image;
• means for extracting a first patch and one or more additional patches from the input medical image based on the identified one or more anatomical landmarks, the first patch and the one or more additional patches depicting different portions of the anatomical object;
• means for extracting features from the first patch and the one or more additional patches using a machine learning based feature extractor network;
• means for detecting an occlusion in the one or more vessels in the first patch based on the extracted features;
• and
• means for outputting results of the detecting.

A non-transitory computer readable medium storing computer program instructions, the computer program instructions when executed by a processor cause the processor to perform operations comprising:

• receiving an input medical image of one or more vessels in an anatomical object of a patient;
• identifying one or more anatomical landmarks in the input medical image;
• extracting a first patch and one or more additional patches from the input medical image based on the identified one or more anatomical landmarks, the first patch and the one or more additional patches depicting different portions of the anatomical object;
• extracting features from the first patch and the one or more additional patches using a machine learning based feature extractor network;
• detecting an occlusion in the one or more vessels in the first patch based on the extracted features;
• and
• outputting results of the detecting.