TY - GEN
T1 - Automated basal cell carcinoma detection in high-definition optical coherence tomography
AU - Li, Annan
AU - Cheng, Jun
AU - Yow, Ai Ping
AU - Srivastava, Ruchir
AU - Wong, Damon Wing Kee
AU - Tey, Hong Liang
AU - Liu, Jiang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/13
Y1 - 2016/10/13
N2 - 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 between HD-OCT images and histopathological architecture have been found. Therefore it is possible to automatically detect BCC using HD-OCT. This paper 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 well demonstrated on a dataset of 5,040 images. It can therefore serve as an automatic tool for screening BCC.
AB - 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 between HD-OCT images and histopathological architecture have been found. Therefore it is possible to automatically detect BCC using HD-OCT. This paper 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 well demonstrated on a dataset of 5,040 images. It can therefore serve as an automatic tool for screening BCC.
UR - http://www.scopus.com/inward/record.url?scp=85009145352&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2016.7591332
DO - 10.1109/EMBC.2016.7591332
M3 - Conference contribution
C2 - 28268917
AN - SCOPUS:85009145352
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2885
EP - 2888
BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Y2 - 16 August 2016 through 20 August 2016
ER -