公开(公告)号：WO2023058067A1

公开(公告)日：2023-04-13

申请号：PCT/IN2022/050904

申请日：2022-10-07

Applicant: QURE.AI TECHNOLOGIES PRIVATE LIMITED

Inventor： WARIER, Prashant ,  MODI, Ankit ,  PUTHA, Preetham ,  VANAPALLI, Prakash ,  CHALLA, Vikash

IPC: G06T7/00 ,  G16H30/40 ,  G06N20/00 ,  A61B6/032 ,  A61B6/50 ,  A61B6/5217 ,  A61B6/5223 ,  A61B6/5258 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30064 ,  G06T5/002 ,  G06T7/0012 ,  G06T7/0016 ,  G06T7/11 ,  G06T7/40 ,  G06T7/62 ,  G06V10/25 ,  G06V10/273 ,  G06V10/75 ,  G06V10/82 ,  G06V2201/03 ,  G16H10/60 ,  G16H50/20 ,  G16H50/30

Abstract: Disclosed is a system (102) and a method for monitoring a CT scan image. A CT scan image may be resampled into a plurality of slices using a bilinear interpolation. A region of interest may be identified on each slice using an image processing technique. The region of interest may be masked on each slice using deep learning. Subsequently, a nodule may be detected as the region of interest using the deep learning. Further, a plurality of characteristics associated with the nodule may be identified. Furthermore, an emphysema may be detected in the region of interest on each slice. A malignancy risk score for the patient may be computed. A progress of the nodule may be monitored across subsequent CT scan images. Finally, a report of the patient may be generated.

公开(公告)号：WO2023281538A1

公开(公告)日：2023-01-12

申请号：PCT/IN2022/050627

申请日：2022-07-09

Applicant: QURE.AI TECHNOLOGIES PRIVATE LIMITED

Inventor： PUTHA, Preetham ,  TADEPALLI, Manoj ,  WARIER, Prashant ,  RAO, Pooja ,  SAHU, Rohan

IPC: A61B8/13 ,  G16H30/00 ,  G16H40/67

Abstract: Disclosed is a method (1000) and a system (102) for acquiring a 3D ultrasound image. The method (100) comprises receiving a request to capture a plurality of ultrasound image for a medical test corresponding to a medical condition. The method (1000) further comprises determining a body part corresponding to the medical test. Further, the method (1000) comprises identifying an imaging site particular to the medical test. Furthermore, the method (1000) comprises 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 (1000) comprises converting the plurality of ultrasound image to a 3-Dimensional (3D) ultrasound image in real time.

公开(公告)号：WO2023058065A1

公开(公告)日：2023-04-13

申请号：PCT/IN2022/050902

申请日：2022-10-07

Applicant: QURE.AI TECHNOLOGIES PRIVATE LIMITED

Inventor： WARIER, Prashant ,  MODI, Ankit ,  PUTHA, Preetham ,  VANAPALLI, Prakash ,  THUMMALA, Pradeep Kumar ,  SENAPATHI, Vijay ,  KUMAR, Kunjesh

IPC: A61B6/03 ,  G06T7/00 ,  G16H30/00 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/60 ,  G06V10/25 ,  G06V10/764 ,  G06V10/7788 ,  G06V2201/032 ,  G16H15/00 ,  G16H30/40 ,  G16H40/67 ,  G16H50/20

Abstract: Disclosed is a system (102) and a method for adapting a report of nodules in computed tomography (CT) scan image. A CT scan image may be resampled into a plurality of slices. A plurality of region of interests may be identified on each slice using an image processing technique. Subsequently, a plurality of nodules may be detected in each region of interest using the deep learning. Further, a plurality of characteristics associated with each nodule may be identified. The plurality of nodules may be classified into AI-confirmed nodules and AI-probable nodules based on a malignancy score. Further, feedback associated with the AI-confirmed nodules and the AI-probable may be received form a radiologist. Furthermore, data may be adapted based on the feedback. Finally, a report comprising adapted data may be generated.

公开(公告)号：WO2022249198A1

公开(公告)日：2022-12-01

申请号：PCT/IN2022/050485

申请日：2022-05-24

Applicant: QURE.AI TECHNOLOGIES PRIVATE LIMITED

Inventor： PUTHA, Preetham ,  TADEPALLI, Manoj ,  REDDY, Bhargava ,  RAJ, Tarun ,  JAGIRDAR, Ammar ,  RAO, Pooja ,  WARIER, Prashant

IPC: G06K9/62 ,  G16H30/00 ,  G06N20/00

Abstract: Disclosed is a system and a method for predicting a lung cancer risk based on a chest X-ray. 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：WO2020099941A1

公开(公告)日：2020-05-22

申请号：PCT/IB2019/050317

申请日：2019-01-15

Applicant: QURE.AI TECHNOLOGIES PRIVATE LIMITED

Inventor： PUTHA, Preetham ,  TADEPALLI, Manoj ,  REDDY, Bhargava ,  NIMMADA, Tarun ,  RAO, Pooja ,  WARIER, Prashant

IPC: G06K9/00 ,  A61B5/05

Abstract: This disclosure generally pertains to methods and systems for processing electronic data obtained from imaging or other diagnostic and evaluative medical procedures. 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 configured to detect and localize medical abnormalities on medical imaging scans by a deep learning algorithm.