Invention Grant
- Patent Title: Adaptive local window-based methods for characterizing features of interest in digital images and systems for practicing same
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Application No.: US15465459Application Date: 2017-03-21
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Publication No.: US10420523B2Publication Date: 2019-09-24
- Inventor: Assaf Hoogi , Daniel L. Rubin
- Applicant: The Board of Trustees of the Leland Stanford Junior University
- Applicant Address: US CA Stanford
- Assignee: The Board of Trustees of the Leland Stanford Junior University
- Current Assignee: The Board of Trustees of the Leland Stanford Junior University
- Current Assignee Address: US CA Stanford
- Agency: Bozicevic, Field & Francis LLP
- Agent Brian E. Davy
- Main IPC: A61B6/00
- IPC: A61B6/00 ; A61B5/055 ; A61B6/03 ; G06T7/10 ; G06T7/12 ; G06T7/174 ; G06T7/194 ; A61B5/00

Abstract:
Provided are methods for characterizing a feature of interest in a digital image. In certain aspects, the methods use an adaptive local window and include obtaining an initial contour for a feature of interest, defining a region of interest around the contour, and segmenting the feature of interest by iteratively selecting a size of a local window surrounding each point on the contour. Non-transitory computer readable media and systems that find use in practicing the methods of the present disclosure are also provided.
Public/Granted literature
- US20170270664A1 METHODS FOR CHARACTERIZING FEATURES OF INTEREST IN DIGITAL IMAGES AND SYSTEMS FOR PRACTICING SAME Public/Granted day:2017-09-21
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