公开(公告)号：US20250148596A1

公开(公告)日：2025-05-08

申请号：US18935726

申请日：2024-11-04

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Swetha Tanamala ,  Sahil Sahil ,  Ravi Kumar Kushawaha

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/82

Abstract: The present subject matter relates to a system (100) and a method (300) for classifying a type of fracture on musculoskeletal X-ray image (101). The system (100) employs a data collection module, a fracture-type classification module including a classification model (207) and a segmentation model (208) based on an artificial intelligence. The data collection module (205) may collect data corresponding to input X-ray images (101), which are then analyzed by a fracture-type classification module (206) using the classification model (207) and the segmentation model (208). Further, the classification model (207) may calculate the classification score and the segmentation module (208) may calculate the segmentation score. The fracture-type classification module may generate the fracture-type score based on the classification score and segmentation score. The fracture-type classification module may be configured for comparing the fracture-type score with a threshold value for each fracture part separately to classify the type of fracture.

公开(公告)号：US11861832B2

公开(公告)日：2024-01-02

申请号：US18073697

申请日：2022-12-02

Applicant: Qure.ai Technologies Private Limited

Inventor： Prashant Warier ,  Ankit Modi ,  Preetham Putha ,  Prakash Vanapalli ,  Vikash Challa ,  Ranjana Devi ,  Ritvik Jain

IPC: G06T7/00 ,  A61B6/00 ,  G06T7/11 ,  G06V10/25 ,  G06T5/00 ,  G16H30/20

CPC classification number: G06T7/0012 ,  A61B6/50 ,  A61B6/5217 ,  A61B6/5258 ,  A61B6/5294 ,  G06T5/002 ,  G06T7/11 ,  G06V10/25 ,  G16H30/20 ,  G06T2207/10081 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30064 ,  G06T2207/30096

Abstract: Disclosed is a system and a method for determining a brock score. A CT scan image may be resampled into a plurality of slices using a bilinear interpolation. A nodule may be detected on one or more of the plurality of slices. A region of interest associated with the nodule may be identified using an image processing technique. Further, a nodule segmentation may be performed to remove an area surrounding the region of interest. Subsequently, a plurality of characteristics associated with the nodule may be identified automatically using a deep learning model. Finally, a brock score for the patient may be determined based on the plurality of characteristics and demographic data of the patient.

公开(公告)号：US11636596B1

公开(公告)日：2023-04-25

申请号：US17986066

申请日：2022-11-14

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Sasank Chilamkurthy ,  Satish Kumar Golla ,  Swetha Tanamala ,  Ujjwal Upadhyay

IPC: G06T7/00 ,  G06T3/40 ,  G06T5/10 ,  G06T7/11 ,  G16H50/20 ,  G06V10/25

Abstract: A system and a method for monitoring a brain CT scan image using ASPECTS score. The method includes receiving the brain CT scan image of a patient. Further, a basal ganglia region and a corona radiata level are identified in a plurality of slices in the brain CT scan image. Furthermore, a plurality of anatomical regions, a plurality of infarcts and a plurality of black regions are segmented using deep learning. Subsequently, an overlapping region across the plurality of slices is determined based on the plurality of anatomical regions, the plurality of infarcts, and the plurality of black regions. The overlapping region and a predefined threshold are used to compute an ASPECTS score. The ASPECTS score is further used to recommend a course of action to the patient.

公开(公告)号：US11501437B1

公开(公告)日：2022-11-15

申请号：US17858191

申请日：2022-07-06

Applicant: Qure.ai Technologies Private Limited

Inventor： Ujjwal Upadhyay ,  Satish Kumar Golla ,  Swetha Tanamala ,  Sasank Chilamkurthy ,  Preetham Putha

IPC: G06T7/00 ,  G16H30/40 ,  G16H50/20 ,  G06T7/11

Abstract: A system and a method for monitoring a brain CT scan image using ASPECTS score. The method includes receiving the brain CT scan image of a patient. Further, a basal ganglia region and a corona radiata level are identified in a plurality of slices in the brain CT scan image. Furthermore, a plurality of anatomical regions and a plurality of infarcts are segmented using deep learning. Subsequently, an overlapping region across the plurality of slices is determined based on the plurality of anatomical regions and the plurality of infarcts. The overlapping region and a predefined threshold are used to compute an ASPECTS score. The ASPECTS score is further used to recommend a course of action to the patient.

公开(公告)号：US11276173B1

公开(公告)日：2022-03-15

申请号：US17383845

申请日：2021-07-23

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Manoj Tadepalli ,  Bhargava Reddy ,  Tarun Raj ,  Ammar Jagirdar ,  Pooja Rao ,  Prashant Warier

IPC: G06T7/00 ,  A61B6/00 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G06N3/08 ,  G06T7/11 ,  G16H50/70 ,  G16H10/60 ,  G16H70/60

Abstract: A system and method for predicting a lung cancer risk based on a chest X-ray in which a nodule is detected in a chest of a patient based on an analysis of the chest X-ray using an image processing technique. A region of interest associated with the nodule is identified using the image processing technique. The region of interest is further analyzed using deep learning to determine a plurality of characteristics associated with the nodule. The plurality of characteristics comprises a size of the nodule, a calcification in the nodule, a homogeneity of the nodule and a spiculation of the nodule. Further, the plurality of characteristics is compared with a trained data model using deep learning. Based on the comparison, a risk score associated with the nodule is generated. Further, the lung cancer risk is predicted when the risk score exceeds a predefined threshold value.

公开(公告)号：US20250148597A1

公开(公告)日：2025-05-08

申请号：US18935765

申请日：2024-11-04

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Swetha Tanamala ,  Sahil Sahil ,  Ravi Kumar Kushawaha

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/82 ,  G06V40/10

Abstract: An invention relates to a system (100) for classifying presence of fracture and body parts on musculoskeletal X-ray. The system (100) is based on an artificial intelligence for targeting fracture classification and body part. Further, the system comprises a data collection module (205) and a fracture classification module (206). Furthermore, the fracture classification module (206) may comprise a classification model (207) and a segmentation model (208). The classification model (207) may be configured to generate a classification score and the segmentation model (208) may be configured to generate segmentation score. The fracture classification module (206) may be configured to generate 10 a fracture score (403) and a body part score (404). The fracture classification module (206) may be configured to compare said scores (403, 404) against threshold values to classify fracture presence and classify body parts. The system (100) may enhance the efficiency and accuracy of fracture diagnosis in X-ray images.

公开(公告)号：US20240127435A1

公开(公告)日：2024-04-18

申请号：US18371460

申请日：2023-09-22

Applicant: Qure.ai Technologies Private Limited

Inventor： Prashant Warier ,  Rohan Sahu ,  Ashish Mittal ,  Kautuk Trivedi ,  Preetham Putha ,  Manoj Tadepalli

IPC: G06T7/00 ,  G06T7/11 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G16H50/20 ,  G06T2207/10132 ,  G06T2207/20081 ,  G06T2207/30101

Abstract: The present subject matter discloses a system and method for automatically detecting and quantifying a plaque/stenosis in a vascular ultrasound scan data in real time using Deep learning models. The system receives a video data and selects one or more frames/images for further processing to detect and quantify the plaque in the artery. Based on the selected one or more frames, the system detects a region of interest (ROI) and further processes the ROI. The system selects end points of a deposits of the plaque by taking a maximum length of the plaque in the artery/plaque boundary and determines the orientation of the vascular ultrasound scan. Based on the orientation and the selected end points, the system determines a vessel/artery boundary to identify a size of the plaque. Based on the determined vessel boundary and the orientation, the system determines plaque segments and measures parameters of the plaque.

公开(公告)号：US11508065B2

公开(公告)日：2022-11-22

申请号：US17207598

申请日：2021-03-19

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Manoj Tadepalli ,  Bhargava Reddy ,  Tarun Raj ,  Ammar Jagirdar ,  Pooja Rao ,  Prashant Warier

IPC: G06N3/08 ,  G06T7/00 ,  G06K9/62 ,  G06N3/04

Abstract: This disclosure generally pertains to methods and systems for automatically detecting acquisition errors in a medical image using machine learning. Certain embodiments relate to methods for the development of deep learning algorithms that perform machine recognition of specific features and conditions in imaging and other medical data. Another embodiment provides systems for detecting acquisition errors in an X-ray image, the system comprising a non-transitory computer-readable medium storing a preprocessing quality control module that, when executed by at least one electronic processor, is configured to generate associated classifications identifying characteristics of the medical image.

公开(公告)号：US11308612B2

公开(公告)日：2022-04-19

申请号：US16889412

申请日：2020-06-01

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Manoj Tadepalli ,  Bhargava Reddy ,  Tarun Raj ,  Ammar Jagirdar ,  Pooja Rao ,  Prashant Warier

IPC: G06T7/00 ,  G06K9/62 ,  G06T7/11 ,  G06K9/32 ,  G06F40/20 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G16H50/70 ,  G16H50/80 ,  G06T7/70 ,  A61B6/00 ,  C12Q1/689

Abstract: This disclosure generally pertains to systems and methods for detection of infectious respiratory diseases by implementation of an automated X-rays-based triage approach alongside algorithmic clinical sample pooling for molecular diagnosis. Certain embodiments relate to methods for the development of deep learning algorithms that perform machine recognition of specific features and conditions in chest X-ray imaging data. The chest X-ray imaging data is used to guide the pooling strategy of clinical samples for a molecular test.

公开(公告)号：US11278260B1

公开(公告)日：2022-03-22

申请号：US17411285

申请日：2021-08-25

Applicant: Qure.ai Technologies Private Limited

Inventor： Preetham Putha ,  Manoj Tadepalli ,  Prashant Warier ,  Pooja Rao ,  Rohan Sahu

IPC: A61B5/00 ,  A61B8/00 ,  A61B8/08 ,  A61B90/00 ,  G01S15/89 ,  G06T19/00 ,  G16H50/20 ,  G06T7/00

Abstract: A method and a system for acquiring a 3D ultrasound image. The method includes receiving a request to capture a plurality of ultrasound image for a medical test corresponding to a medical condition. The method further includes determining a body part corresponding to the medical test. Further, the method includes identifying an imaging site particular to the medical test. Furthermore, the method includes providing a navigational guidance to the user in real time for positioning a handheld ultrasound device. Subsequently, the user is assisted to capture the plurality of ultrasound image of the imaging site in real time using deep learning. Further, the plurality of ultrasound images of the imaging site is captured. Finally, the method includes converting the plurality of ultrasound image to a 3-Dimensional (3D) ultrasound image in real time.