TY - GEN
T1 - Spatial Probabilistic Distribution Map Based 3D FCN for Visual Pathway Segmentation
AU - Zhao, Zhiqi
AU - Ai, Danni
AU - Li, Wenjie
AU - Fan, Jingfan
AU - Song, Hong
AU - Wang, Yongtian
AU - Yang, Jian
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Image-guided surgery has become an important aid in sinus and skull base surgery. In the preoperative planning stage, vital structures, such as the visual pathway, must be segmented to guide the surgeon during surgery. However, owing to the elongated structure and low contrast in medical images, automatic segmentation of the visual pathway is challenging. This study proposed a novel method based on 3D fully convolutional network (FCN) combined with a spatial probabilistic distribution map (SPDM) for visual pathway segmentation in magnetic resonance imaging. Experimental results indicated that compared with the FCN that relied only on image intensity information, the introduction of an SPDM effectively overcame the problem of low contrast and blurry boundary and achieved better segmentation performance.
AB - Image-guided surgery has become an important aid in sinus and skull base surgery. In the preoperative planning stage, vital structures, such as the visual pathway, must be segmented to guide the surgeon during surgery. However, owing to the elongated structure and low contrast in medical images, automatic segmentation of the visual pathway is challenging. This study proposed a novel method based on 3D fully convolutional network (FCN) combined with a spatial probabilistic distribution map (SPDM) for visual pathway segmentation in magnetic resonance imaging. Experimental results indicated that compared with the FCN that relied only on image intensity information, the introduction of an SPDM effectively overcame the problem of low contrast and blurry boundary and achieved better segmentation performance.
KW - 3D fully convolutional network
KW - Optic nerve
KW - Spatial probabilistic distribution map
KW - Visual pathway segmentation
UR - http://www.scopus.com/inward/record.url?scp=85076922123&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-34110-7_42
DO - 10.1007/978-3-030-34110-7_42
M3 - Conference contribution
AN - SCOPUS:85076922123
SN - 9783030341091
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 509
EP - 518
BT - Image and Graphics - 10th International Conference, ICIG 2019, Proceedings, Part 2
A2 - Zhao, Yao
A2 - Lin, Chunyu
A2 - Barnes, Nick
A2 - Chen, Baoquan
A2 - Westermann, Rüdiger
A2 - Kong, Xiangwei
PB - Springer
T2 - 10th International Conference on Image and Graphics, ICIG 2019
Y2 - 23 August 2019 through 25 August 2019
ER -
