Systems and methods for multiple instance learning for classification and localization in biomedical imaging

A method of comprising:

• identifying, by a computing system, a plurality of tiles of a biomedical image subsequent to removal of negative space corresponding to lack of any features within the biomedical image, the biomedical image having one of a presence or an absence of a condition within one or more portions;
• applying, by the computing system, a trained aggregation model having a plurality of parameters to the plurality of tiles in sequence;
• determining, by the computing system, from applying the trained aggregation model to the plurality of tiles in sequence, a classification result indicating one of the biomedical image having at least one feature corresponding to the presence of the condition or the biomedical image corresponding to the absence of the condition;
• and
• providing, by the computing system, the classification result for the biomedical image.

A system for classifying biomedical images, comprising:

• a computing system having one or more processors coupled with memory, configured to:
• identify a plurality of tiles of a biomedical image subsequent to removal of negative space corresponding to lack of any features within the biomedical image, the biomedical image having one of a presence or an absence of a condition within one or more portions;
• apply a trained aggregation model having a plurality of parameters to the plurality of tiles in sequence;
• determine, from applying the trained aggregation model to the plurality of tiles in sequence, a classification result indicating one of the biomedical image having at least one feature corresponding to the presence of the condition or the biomedical image corresponding to the absence of the condition;
• and
• provide the classification result for the biomedical image.