Digital image analysis using multi-step analysis
DCFirst Claim
1. A computer-implemented feature extraction method for classifying pixels of a digitized pathology image, the method to be performed by a system comprising at least one processor and at least one memory, the method comprising:
- generating a plurality of characterized pixels from a digitized pathology image;
determining by the system in a first step feature analysis a first region and a first remainder region of the digitized pathology image based on the plurality of characterized pixels;
determining by the system, in a plurality of subsequent feature analysis steps, subsequent regions and subsequent remainder regions, wherein each feature analysis step determines a corresponding image region and a corresponding remainder region based on a remainder region determined by an earlier feature analysis step; and
classifying by the system part or all of the digitized pathology image based on the determined first region, and the determined subsequent regions.
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Abstract
Systems and methods for implementing a multi-step image recognition framework for classifying digital images are provided. The provided multi-step image recognition framework utilizes a gradual approach to model training and image classification tasks requiring multi-dimensional ground truths. A first step of the multi-step image recognition framework differentiates a first image region from a remainder image region. Each subsequent step operates on a remainder image region from the previous step. The provided multi-step image recognition framework permits model training and image classification tasks to be performed more accurately and in a less resource intensive fashion than conventional single-step image recognition frameworks.
41 Citations
18 Claims
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1. A computer-implemented feature extraction method for classifying pixels of a digitized pathology image, the method to be performed by a system comprising at least one processor and at least one memory, the method comprising:
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generating a plurality of characterized pixels from a digitized pathology image; determining by the system in a first step feature analysis a first region and a first remainder region of the digitized pathology image based on the plurality of characterized pixels; determining by the system, in a plurality of subsequent feature analysis steps, subsequent regions and subsequent remainder regions, wherein each feature analysis step determines a corresponding image region and a corresponding remainder region based on a remainder region determined by an earlier feature analysis step; and classifying by the system part or all of the digitized pathology image based on the determined first region, and the determined subsequent regions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system or image recognition analysis of a digital image comprising:
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a memory having program instructions and data storage space; a processor configured to use the program instructions to perform the steps of; generating a plurality of characterized pixels from a digitized pathology image; determining in a first step feature analysis a first region and a first remainder region of the digitized pathology image based on the plurality of characterized pixels; determining in a plurality of subsequent feature analysis steps subsequent regions and subsequent remainder regions, wherein each feature analysis steps determines a corresponding image region and a corresponding remainder region based on a remainder region determined by an earlier feature analysis step; and classifying part or all of the digitized pathology image based on the determined first region, and the determined subsequent regions. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification