Automatic recognition of different tissue types in histological images is an essential part in the digital pathology toolbox. Texture analysis is commonly used to address this problem; mainly in the context of estimating the tumour/stroma ratio on histological samples. i) Identify the best image descriptor with Tamura Features that can be used and elaborate on the manner in which the feature can be used to detect the tissues in the histological images. ii) Draft the complete algorithm/pseudocode for the system.
Automatic recognition of different tissue types in histological images is an essential part in the digital pathology toolbox. Texture analysis is commonly used to address this problem; mainly in the context of estimating the tumour/stroma ratio on histological samples. i) Identify the best image descriptor with Tamura Features that can be used and elaborate on the manner in which the feature can be used to detect the tissues in the histological images. ii) Draft the complete algorithm/pseudocode for the system.
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Automatic recognition of different tissue types in histological images is an essential part in the digital pathology toolbox. Texture analysis is commonly used to address this problem; mainly in the context of estimating the tumour/stroma ratio on histological samples.
i) Identify the best image descriptor with Tamura Features that can be used and elaborate on the manner in which the feature can be used to detect the tissues in the histological images.
ii) Draft the complete
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