Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Basal cell carcinoma (BCC) is the most common non-melanoma skin cancer. Conventional diagnosis of BCC requires invasive biopsies. Recently, a high-definition optical coherence tomography (HD-OCT) technique has been developed, which provides a non-invasive in vivo imaging method of skin. Good agreements of BCC features beten HD-OCT images and histopathological architecture have been found. Therefore it is possible to automatically detect BCC using HD-OCT.  presents a novel BCC detection method that consists of four steps: graph based skin surface segmentation, surface flattening, deep feature extraction and the BCC classification. The effectiveness of the proposed method is ll demonstrated on a dataset of 5,040 images. It can therefore serve as an automatic tool for screening BCC.
['Annan Li', 'Jun Cheng', 'Ai Ping Yow', 'Ruchir Srivastava', 'Damon Wing Kee Wong', 'Hong Liang Tey', 'Jiang Liu']
I am writing a research paper on a idea Automated basal cell carcinoma detection in high-definition optical coherence tomography
[{"from": "human", "value": "I am writing a research paper on a idea Automated basal cell carcinoma detection in high-definition optical coherence tomography"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Basal cell carcinoma (BCC) is the most common non-melanoma skin cancer. Conventional diagnosis of BCC requires invasive biopsies. Recently, a high-definition optical coherence tomography (HD-OCT) technique has been developed, which provides a non-invasive in vivo imaging method of skin. Good agreements of BCC features beten HD-OCT images and histopathological architecture have been found. Therefore it is possible to automatically detect BCC using HD-OCT.  presents a novel BCC detection method that consists of four steps: graph based skin surface segmentation, surface flattening, deep feature extraction and the BCC classification. The effectiveness of the proposed method is ll demonstrated on a dataset of 5,040 images. It can therefore serve as an automatic tool for screening BCC."}]