US 12,412,323 B2
System and method for complex input data configurations for imaging applications
Danyal Fareed Bhutto, Boston, MA (US); Matthew S. Rosen, Somerville, MA (US); Neha Koonjoo, Boston, MA (US); and Bo Zhu, Palo Alto, CA (US)
Assigned to The General Hospital Corporation, Boston, MA (US); and Trustees of Boston University, Boston, MA (US)
Filed by The General Hospital Corporation, Boston, MA (US); and Trustees of Boston University, Boston, MA (US)
Filed on Apr. 24, 2023, as Appl. No. 18/305,697.
Claims priority of provisional application 63/334,077, filed on Apr. 22, 2022.
Prior Publication US 2023/0342996 A1, Oct. 26, 2023
Int. Cl. G06T 11/00 (2006.01); A61B 5/055 (2006.01); G16H 30/40 (2018.01)
CPC G06T 11/006 (2013.01) [A61B 5/055 (2013.01); G16H 30/40 (2018.01); G06T 2210/41 (2013.01); G06T 2211/421 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for medical imaging, comprising:
receiving raw sensor data acquired from a patient using a medical imaging modality;
applying the raw sensor data to an input layer of a neural network to generate an input vector, wherein the input layer of the neural network orders the input vector such that a real component and an imaginary component of each sample in the raw sensor data are adjacent to each other;
applying the input vector to a first convolutional layer of the neural network to generate a filtered input vector;
applying the filtered input vector to at least one fully connected layer of the neural network to generate a matrix;
applying the matrix to at least one additional convolutional layer of the neural network different from the first convolutional layer to generate a medical image of the patient; and
displaying the medical image of the patient.