Patent ID: 11861832
Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITED
Field: Medical technology (Instruments)
Classification: CPC G  A | IPC A  G

Claim 0:
1. A method to determine a brock score for a patient:
receiving, by a processor, a Computed Tomography (CT) scan image related to a chest region of the patient;
resampling, by the processor, the CT scan image into a plurality of slices by applying a bilinear interpolation on a distance weighted average of surrounded pixel values;
detecting, by the processor, a nodule on one or more of the plurality of slices based on an analysis of the plurality of slices using a first deep learning, wherein the first deep learning is trained using historical CT scans and historical modules associated with a set of patients, and wherein the first deep learning model is configured to detect patterns related to the historical nodules in the historical CT scans and process the one or more slices;
identifying, by the processor, a region of interest associated with the nodule based on an analysis of the nodule using an image processing technique;
masking, by the processor, the region of interest to perform a nodule segmentation by removing an area, including at least one of black areas and fatty tissues, surrounding the region of interest, wherein the nodule segmentation is performed using the first deep learning model;
automatically determining, by the processor, a plurality of characteristics associated with the region of interest using a second deep learning model, wherein the second deep learning model is trained using historical characteristics including a historical size of nodules, historical location of nodules, a historical speculation of nodules, and a historical texture of nodules associated with the set of patients, wherein the plurality of characteristics comprises a location of the nodule, a texture of the nodule, a size of the nodule, a speculation of the nodule, and number of nodules present in the CT scan image; and
determining, by the processor, a brock score for the patient automatically in real-time based on the plurality of characteristics and demographics data of the patient.