Cell quantization tool for anterior chamber OCT images

Yeongseop Lee; Taeseen Kang; Yongseop Han; Jinhyun Kim; Kyong Hoon Kim; Seongjin Lee

doi:10.5370/KIEE.2020.69.7.1073

Cell quantization tool for anterior chamber OCT images

Yeongseop Lee, Taeseen Kang, Yongseop Han, Jinhyun Kim, Kyong Hoon Kim, Seongjin Lee

Research output: Contribution to journal › Article › peer-review

Abstract

In general, ophthalmologists visually grade the state of a patient by counting the cells within the anterior chamber OCT image. The manual cell counting method is highly inaccurate and spends a lot of time to determine the progress of the patient. In this work, we develop a new tool to count cells in anterior chamber OCT images to aid doctors in analyzing the state of patients. We exploit image processing to remove noises from images, segment the anterior chamber, and quantize the cells in OCT images. We also provide statistics to aid the doctors in determining the progress of the patients.

Original language	English
Pages (from-to)	1073-1080
Number of pages	8
Journal	Transactions of the Korean Institute of Electrical Engineers
Volume	69
Issue number	7
DOIs	https://doi.org/10.5370/KIEE.2020.69.7.1073
State	Published - Jul 2020

Keywords

Anterior Chamber
Cell Count
Computer Vision
SD-OCT

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title = "Cell quantization tool for anterior chamber OCT images",

abstract = "In general, ophthalmologists visually grade the state of a patient by counting the cells within the anterior chamber OCT image. The manual cell counting method is highly inaccurate and spends a lot of time to determine the progress of the patient. In this work, we develop a new tool to count cells in anterior chamber OCT images to aid doctors in analyzing the state of patients. We exploit image processing to remove noises from images, segment the anterior chamber, and quantize the cells in OCT images. We also provide statistics to aid the doctors in determining the progress of the patients.",

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AU - Lee, Yeongseop

AU - Kang, Taeseen

AU - Han, Yongseop

AU - Kim, Jinhyun

AU - Kim, Kyong Hoon

AU - Lee, Seongjin

N1 - Publisher Copyright: © Korean Institute of Electrical Engineers

PY - 2020/7

Y1 - 2020/7

N2 - In general, ophthalmologists visually grade the state of a patient by counting the cells within the anterior chamber OCT image. The manual cell counting method is highly inaccurate and spends a lot of time to determine the progress of the patient. In this work, we develop a new tool to count cells in anterior chamber OCT images to aid doctors in analyzing the state of patients. We exploit image processing to remove noises from images, segment the anterior chamber, and quantize the cells in OCT images. We also provide statistics to aid the doctors in determining the progress of the patients.

AB - In general, ophthalmologists visually grade the state of a patient by counting the cells within the anterior chamber OCT image. The manual cell counting method is highly inaccurate and spends a lot of time to determine the progress of the patient. In this work, we develop a new tool to count cells in anterior chamber OCT images to aid doctors in analyzing the state of patients. We exploit image processing to remove noises from images, segment the anterior chamber, and quantize the cells in OCT images. We also provide statistics to aid the doctors in determining the progress of the patients.

KW - Anterior Chamber

KW - Cell Count

KW - Computer Vision

KW - SD-OCT

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JO - Transactions of the Korean Institute of Electrical Engineers

JF - Transactions of the Korean Institute of Electrical Engineers

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Cell quantization tool for anterior chamber OCT images

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Keywords

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