Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  propose a visual phrase learning scheme to learn an optimal visual composite of anatomical components/parts from CT colonography images for computer-aided detection. The key idea is to utilize the anatomical parts of human body from medical images and associate them with biological targets of interest (organs, cancers, lesions, etc.) for joint detection and recognition. These anatomical parts of the human body are not necessarily near each other regarding their physical locations, and they serve more like a human body navigation system for detection and recognition. To show the effectiveness of the proposed learning scheme,  applied it to two subproblems in computed tomographic colonography: teniae detection and classification of colorectal polyp candidates. Experimental results shod its efficacy.
['Shijun Wang', 'Matthew McKenna', 'Zhuoshi Wei', 'Jiamin Liu', 'Peter Liu', 'Ronald M. Summers']
I am writing a research paper on a idea Visual Phrase Learning and its Application in Computed Tomographic Colonography
[{"from": "human", "value": "I am writing a research paper on a idea Visual Phrase Learning and its Application in Computed Tomographic Colonography"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this work,  propose a visual phrase learning scheme to learn an optimal visual composite of anatomical components/parts from CT colonography images for computer-aided detection. The key idea is to utilize the anatomical parts of human body from medical images and associate them with biological targets of interest (organs, cancers, lesions, etc.) for joint detection and recognition. These anatomical parts of the human body are not necessarily near each other regarding their physical locations, and they serve more like a human body navigation system for detection and recognition. To show the effectiveness of the proposed learning scheme,  applied it to two subproblems in computed tomographic colonography: teniae detection and classification of colorectal polyp candidates. Experimental results shod its efficacy."}]