TY - GEN
T1 - Focal biologically inspired feature for glaucoma type classification
AU - Cheng, Jun
AU - Tao, Dacheng
AU - Liu, Jiang
AU - Wong, Damon Wing Kee
AU - Lee, Beng Hai
AU - Baskaran, Mani
AU - Wong, Tien Yin
AU - Aung, Tin
PY - 2011
Y1 - 2011
N2 - Glaucoma is an optic nerve disease resulting in loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2% images from open angle glaucoma and 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.
AB - Glaucoma is an optic nerve disease resulting in loss of vision. There are two common types of glaucoma: open angle glaucoma and angle closure glaucoma. Glaucoma type classification is important in glaucoma diagnosis. Ophthalmologists examine the iridocorneal angle between iris and cornea to determine the glaucoma type. However, manual classification/grading of the iridocorneal angle images is subjective and time consuming. To save workload and facilitate large-scale clinical use, it is essential to determine glaucoma type automatically. In this paper, we propose to use focal biologically inspired feature for the classification. The iris surface is located to determine the focal region. The association between focal biologically inspired feature and angle grades is built. The experimental results show that the proposed method can correctly classify 85.2% images from open angle glaucoma and 84.3% images from angle closure glaucoma. The accuracy could be improved close to 90% with more images included in the training. The results show that the focal biologically inspired feature is effective for automatic glaucoma type classification. It can be used to reduce workload of ophthalmologists and diagnosis cost.
UR - http://www.scopus.com/inward/record.url?scp=80053496197&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23626-6_12
DO - 10.1007/978-3-642-23626-6_12
M3 - Conference contribution
C2 - 22003688
AN - SCOPUS:80053496197
SN - 9783642236259
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 91
EP - 98
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Y2 - 18 September 2011 through 22 September 2011
ER -
