Systems and methods for artificial intelligence-based image analysis for detection and characterization of lesions

A method for automatically processing 3D images of a subject to identify and/or characterize cancerous lesions within the subject, the method comprising:

• (a) receiving, by a processor of a computing device, a 3D functional image of the subject obtained using a functional imaging modality;
• (b) receiving, by the processor, a 3D anatomical image of the subject obtained using an anatomical imaging modality, wherein the 3D anatomical image comprises a graphical representation of tissue within the subject;
• (c) automatically detecting, by the processor, using a machine learning module, one or more hotspots within the 3D functional image, each hotspot corresponding to a local region of elevated intensity with respect to its surrounding and representing a potential cancerous lesion within the subject, thereby creating a 3D hotspot map, identifying, for each hotspot, a corresponding 3D hotspot volume within the 3D functional image,
• wherein the machine learning module receives at least two channels of input, said input channels comprising a first input channel corresponding to at least a portion of the 3D functional image and a second input channel corresponding to at least a portion of the 3D anatomical image and/or anatomical information derived therefrom, and generates the 3D hotspot map as output;
• and
• (d) storing and/or providing, for display and/or further processing, the 3D hotspot map.

A system for automatically processing 3D images of a subject to identify and/or characterize cancerous lesions within the subject, the system comprising:

• a processor of a computing device;
• and
• a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
• (a) receive a 3D functional image of the subject obtained using a functional imaging modality;
• (b) automatically detect, using a machine learning module, one or more hotspots within the 3D functional image, each hotspot corresponding to a local region of elevated intensity with respect to its surrounding and representing a potential cancerous lesion within the subject, thereby creating a 3D hotspot map, identifying, for each hotspot, a corresponding 3D hotspot volume within the 3D functional image, wherein the machine learning module receives, as input, at least a portion of the 3D functional image and generates the 3D hotspot map as output;
• and
• (c) store and/or provide, for display and/or further processing, the 3D hotspot map.

A system for automatically processing 3D images of a subject to identify and/or characterize cancerous lesions within the subject, the system comprising:

• a processor of a computing device;
• and
• a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
• (a) receive a 3D functional image of the subject obtained using a functional imaging modality;
• (b) receive a 3D anatomical image of the subject obtained using an anatomical imaging modality, wherein the 3D anatomical image comprises a graphical representation of tissue within the subject;
• (c) automatically detect, using a machine learning module, one or more hotspots within the 3D functional image, each hotspot corresponding to a local region of elevated intensity with respect to its surrounding and representing a potential cancerous lesion within the subject, thereby creating a 3D hotspot map, identifying, for each hotspot, a corresponding 3D hotspot volume within the 3D functional image,
• wherein the machine learning module receives at least two channels of input, said input channels comprising a first input channel corresponding to at least a portion of the 3D functional image and a second input channel corresponding to at least a portion of the 3D anatomical image and/or anatomical information derived therefrom, and generates the 3D hotspot map as output;
• and
• (d) store and/or provide, for display and/or further processing, the 3D hotspot map.