Pupil localization for ophthalmic diagnosis using anchor ellipse regression

Horng Horng Lin, Zheng Yi Li, Min-Hsiu Shih, Yung-Nien Sun, Ting Li Shen

研究成果: Conference contribution

摘要

Recent developments of deep neural networks, such as Mask R-CNN, have shown significant advances in simultaneous object detection and segmentation. We thus apply deep learning to pupil localization for ophthalmic diagnosis and propose a novel anchor ellipse regression approach based on region proposal network and Mask R-CNN for detecting pupils, estimating pupil shape parameters, and segmenting pupil regions at the same time in infrared images. This new extension of anchor ellipse regression for Mask R-CNN is demonstrated to be effective in size and rotation estimations of elliptical objects, as well as in object detections and segmentations, by experiments. Temporal pupil size estimations by using the proposed approach for normal and abnormal subjects give meaningful indices of pupil size changes for ophthalmic diagnosis.

原文English
主出版物標題Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9784901122184
DOIs
出版狀態Published - 2019 五月 1
事件16th International Conference on Machine Vision Applications, MVA 2019 - Tokyo, Japan
持續時間: 2019 五月 272019 五月 31

出版系列

名字Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019

Conference

Conference16th International Conference on Machine Vision Applications, MVA 2019
國家Japan
城市Tokyo
期間19-05-2719-05-31

指紋

Anchors
Masks
Infrared radiation
Experiments
Object detection

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Signal Processing
  • Computer Vision and Pattern Recognition

引用此文

Lin, H. H., Li, Z. Y., Shih, M-H., Sun, Y-N., & Shen, T. L. (2019). Pupil localization for ophthalmic diagnosis using anchor ellipse regression. 於 Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019 [8757976] (Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/MVA.2019.8757976
Lin, Horng Horng ; Li, Zheng Yi ; Shih, Min-Hsiu ; Sun, Yung-Nien ; Shen, Ting Li. / Pupil localization for ophthalmic diagnosis using anchor ellipse regression. Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019).
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title = "Pupil localization for ophthalmic diagnosis using anchor ellipse regression",
abstract = "Recent developments of deep neural networks, such as Mask R-CNN, have shown significant advances in simultaneous object detection and segmentation. We thus apply deep learning to pupil localization for ophthalmic diagnosis and propose a novel anchor ellipse regression approach based on region proposal network and Mask R-CNN for detecting pupils, estimating pupil shape parameters, and segmenting pupil regions at the same time in infrared images. This new extension of anchor ellipse regression for Mask R-CNN is demonstrated to be effective in size and rotation estimations of elliptical objects, as well as in object detections and segmentations, by experiments. Temporal pupil size estimations by using the proposed approach for normal and abnormal subjects give meaningful indices of pupil size changes for ophthalmic diagnosis.",
author = "Lin, {Horng Horng} and Li, {Zheng Yi} and Min-Hsiu Shih and Yung-Nien Sun and Shen, {Ting Li}",
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Lin, HH, Li, ZY, Shih, M-H, Sun, Y-N & Shen, TL 2019, Pupil localization for ophthalmic diagnosis using anchor ellipse regression. 於 Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019., 8757976, Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019, Institute of Electrical and Electronics Engineers Inc., 16th International Conference on Machine Vision Applications, MVA 2019, Tokyo, Japan, 19-05-27. https://doi.org/10.23919/MVA.2019.8757976

Pupil localization for ophthalmic diagnosis using anchor ellipse regression. / Lin, Horng Horng; Li, Zheng Yi; Shih, Min-Hsiu; Sun, Yung-Nien; Shen, Ting Li.

Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8757976 (Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019).

研究成果: Conference contribution

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AU - Shen, Ting Li

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N2 - Recent developments of deep neural networks, such as Mask R-CNN, have shown significant advances in simultaneous object detection and segmentation. We thus apply deep learning to pupil localization for ophthalmic diagnosis and propose a novel anchor ellipse regression approach based on region proposal network and Mask R-CNN for detecting pupils, estimating pupil shape parameters, and segmenting pupil regions at the same time in infrared images. This new extension of anchor ellipse regression for Mask R-CNN is demonstrated to be effective in size and rotation estimations of elliptical objects, as well as in object detections and segmentations, by experiments. Temporal pupil size estimations by using the proposed approach for normal and abnormal subjects give meaningful indices of pupil size changes for ophthalmic diagnosis.

AB - Recent developments of deep neural networks, such as Mask R-CNN, have shown significant advances in simultaneous object detection and segmentation. We thus apply deep learning to pupil localization for ophthalmic diagnosis and propose a novel anchor ellipse regression approach based on region proposal network and Mask R-CNN for detecting pupils, estimating pupil shape parameters, and segmenting pupil regions at the same time in infrared images. This new extension of anchor ellipse regression for Mask R-CNN is demonstrated to be effective in size and rotation estimations of elliptical objects, as well as in object detections and segmentations, by experiments. Temporal pupil size estimations by using the proposed approach for normal and abnormal subjects give meaningful indices of pupil size changes for ophthalmic diagnosis.

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Lin HH, Li ZY, Shih M-H, Sun Y-N, Shen TL. Pupil localization for ophthalmic diagnosis using anchor ellipse regression. 於 Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8757976. (Proceedings of the 16th International Conference on Machine Vision Applications, MVA 2019). https://doi.org/10.23919/MVA.2019.8757976