Invention Grant
- Patent Title: Automated segmentation of organ chambers using deep learning methods from medical imaging
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Application No.: US15294207Application Date: 2016-10-14
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Publication No.: US10521902B2Publication Date: 2019-12-31
- Inventor: Michael Rashidi Avendi , Hamid Jafarkhani , Arash Kheradvar
- Applicant: The Regents of the University of California
- Applicant Address: US CA Oakland
- Assignee: The Regents of the University of California
- Current Assignee: The Regents of the University of California
- Current Assignee Address: US CA Oakland
- Agency: Knobbe, Martens, Olson & Bear LLP
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T3/00 ; G06T7/38 ; G06T7/11 ; G06T7/149
Abstract:
Systems and methods are disclosed for automatically segmenting a heart chamber from medical images of a patient. The system may include one or more hardware processors configured to: obtain image data including at least a representation of the patient's heart; obtain a region of interest from the image data; organize the region of interest into an input vector; apply the input vector through a trained graph; obtain an output vector representing a refined region of interest corresponding to the heart based on the application of the input vector through the trained graph; apply a deformable model on the obtained output vector representing the refined region of interest; and identify a segment of a heart chamber from the application of the deformable model on the obtained output vector.
Public/Granted literature
- US20170109881A1 AUTOMATED SEGMENTATION OF ORGAN CHAMBERS USING DEEP LEARNING METHODS FROM MEDICAL IMAGING Public/Granted day:2017-04-20
Information query
