Patents by Inventor Preetham Putha
Preetham Putha has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11967079Abstract: The present subject matter discloses a system and method for detecting Large Vessel Occlusion (LVO) on a Computational Tomography Angiogram (CTA) automatically. the system comprises a vascular-territory-segmentation module, an ICV segmentation module, MCA-LVO classifier and ICA-LVO classifier. The vascular territory segmentation module is configured to receive a set of CTA images and to mark a territory of vascular segments in the ICV region for each slice of the ROI. The ICV segmentation module is configured to process each slice of the ROI. The processed slices of the ROI are combined to develop a CTA image after application of MIP and the developed CTA image is segmented into a Middle Cerebral Artery (MCA) region and an Internal Cerebral Artery (ICA) region. The MCA-LVO and ICA-LVO classifiers determine presence of the LVO on the received MCA and ICA region using Deep Learning techniques and accordingly the presence of the LVO is reported.Type: GrantFiled: October 12, 2023Date of Patent: April 23, 2024Assignee: Qure.ai Technologies Private LimitedInventors: Shubham Kumar, Arjun Agarwal, Satish Kumar Golla, Swetha Tanamala, Preetham Putha, Sasank Chilamkurthy, Prashant Warier
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SYSTEM AND METHOD FOR DETECTING AND QUANTIFYING A PLAQUE/STENOSIS IN A VASCULAR ULTRASOUND SCAN DATA
Publication number: 20240127435Abstract: 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.Type: ApplicationFiled: September 22, 2023Publication date: April 18, 2024Inventors: Prashant Warier, Rohan Sahu, Ashish Mittal, Kautuk Trivedi, Preetham Putha, Manoj Tadepalli -
Patent number: 11861832Abstract: 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.Type: GrantFiled: December 2, 2022Date of Patent: January 2, 2024Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITEDInventors: Prashant Warier, Ankit Modi, Preetham Putha, Prakash Vanapalli, Vikash Challa, Ranjana Devi, Ritvik Jain
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Publication number: 20230177687Abstract: 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.Type: ApplicationFiled: December 2, 2022Publication date: June 8, 2023Applicant: Qure.ai Technologies Private LimitedInventors: Prashant WARIER, Ankit MODI, Preetham PUTHA, Prakash VANAPALLI, Vikash CHALLA, Ranjana DEVI, Ritvik JAIN
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Patent number: 11636596Abstract: 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.Type: GrantFiled: November 14, 2022Date of Patent: April 25, 2023Assignee: Qure.ai Technologies Private LimitedInventors: Preetham Putha, Sasank Chilamkurthy, Satish Kumar Golla, Swetha Tanamala, Ujjwal Upadhyay
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Patent number: 11521321Abstract: Disclosed is a system 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.Type: GrantFiled: December 3, 2021Date of Patent: December 6, 2022Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITEDInventors: Prashant Warier, Ankit Modi, Preetham Putha, Prakash Vanapalli, Vikash Challa
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Patent number: 11508065Abstract: 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.Type: GrantFiled: March 19, 2021Date of Patent: November 22, 2022Assignee: Qure.ai Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Patent number: 11501437Abstract: 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.Type: GrantFiled: July 6, 2022Date of Patent: November 15, 2022Assignee: Qure.ai Technologies Private LimitedInventors: Ujjwal Upadhyay, Satish Kumar Golla, Swetha Tanamala, Sasank Chilamkurthy, Preetham Putha
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Publication number: 20220245795Abstract: 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.Type: ApplicationFiled: March 19, 2021Publication date: August 4, 2022Applicant: Qure.ai Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Patent number: 11367191Abstract: Disclosed is a system 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.Type: GrantFiled: December 3, 2021Date of Patent: June 21, 2022Inventors: Prashant Warier, Ankit Modi, Preetham Putha, Prakash Vanapalli, Pradeep Kumar Thummala, Vijay Senapathi, Kunjesh Kumar
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Patent number: 11308612Abstract: 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.Type: GrantFiled: June 1, 2020Date of Patent: April 19, 2022Assignee: Qure.ai Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Patent number: 11278260Abstract: 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.Type: GrantFiled: August 25, 2021Date of Patent: March 22, 2022Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITEDInventors: Preetham Putha, Manoj Tadepalli, Prashant Warier, Pooja Rao, Rohan Sahu
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Patent number: 11276173Abstract: 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.Type: GrantFiled: July 23, 2021Date of Patent: March 15, 2022Assignee: QURE.AI TECHNOLOGIES PRIVATE LIMITEDInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Publication number: 20210327055Abstract: 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.Type: ApplicationFiled: June 1, 2020Publication date: October 21, 2021Applicant: Qure.ai Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Patent number: 10755413Abstract: 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.Type: GrantFiled: February 24, 2020Date of Patent: August 25, 2020Assignee: Qure.AI Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Raj, Ammar Jagirdar, Pooja Rao, Prashant Warier
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Patent number: 10733727Abstract: 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.Type: GrantFiled: February 6, 2019Date of Patent: August 4, 2020Assignee: Qure.AI Technologies Private LimitedInventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Nimmada, Pooja Rao, Prashant Warier
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Publication number: 20200151871Abstract: 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.Type: ApplicationFiled: February 6, 2019Publication date: May 14, 2020Inventors: Preetham Putha, Manoj Tadepalli, Bhargava Reddy, Tarun Nimmada, Pooja Rao, Prashant Warier