Abstract: An artificial neural network based platform uses a validated multilayer convolutional network for neurological analysis configured for segmenting data sets of neurological scans of a specific given patient. The validated multilayer convolutional network of the platform includes classification of neurological tissue within classification voxels of at least one patient data set by the validated multilayer convolutional network for neurological analysis with each classification voxel of the at least one patient data set assigned a label, wherein the implementing the validated multilayer convolutional network includes at least one of i) mapping neurologic tissue or ii) mapping of a neurological tumor of a patient.

Abstract: An artificial intelligence based vascular mapping and interventional procedure assisting platform configured to identify at least the femoral artery and the bifurcation point of the femoral artery of a patient based upon dynamic imaging of the patient. The platform may be a stroke management tool in which an angiogram and conventional bloodwork can be inputted into the platform and the platform provides one of i) classification of a stroke and stroke prediction; and whether an interventional procedure is indicated and wherein if interventional procedure is indicated then vascular mapping is provided with bifurcation points and the desired access illustrated together with a listing of accepted or counter indicated closure systems that may be used.

Abstract: A method of implementing an artificial intelligence based imaging platform for cardiopulmonary analysis comprises providing a multilayer convolutional network for cardiopulmonary analysis configured for segmenting data sets of cardiopulmonary scans into resolution voxels; supervised learning and validation of the platform by classification of tissue within classification voxels of a specific given training and validation data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of the training and validation data sets having a predetermined ground truth; and implementing the platform by classification of tissue within classification voxels of a specific given patient data sets by the multilayer convolutional network for cardiopulmonary analysis with each classification voxel of each data set assigned a label. An artificial intelligence based imaging platform implemented according to the method is disclosed.

Abstract: A method of implementing an artificial intelligence based neuroradiology platform for neurological tumor identification comprises providing a multilayer convolutional network for neurological tumor identification configured for segmenting data sets of full neurologic scans into resolution voxels; supervised learning and validation of the platform by classification of tissue within classification voxels of a specific given training and validation data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of the training and validation data sets having a predetermined ground truth; and implementing the platform by classification of tissue within classification voxels of a specific given patient data sets by the multilayer convolutional network for neurological tumor identification with each classification voxel of each data set assigned a label. The platform may be used for T-cell therapy initiation and tracking.