A novel benchmark model for intelligent annotation of spectral-domain optical coherence tomography scans using the example of cyst annotation
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- 作者：Ehsan Shahrian Varnousfaderani ; Jing Wu ; Wolf-Dieter Vogl ; Ana-Maria Philip ; Alessio Montuoro ; Roland Leitner ; Christian Simader ; Sebastian M. Waldstein ; Bianca S. Gerendas ; bianca.gerendas@meduniwien.ac.at" class="auth_mail" title="E-mail the corresponding author ; Ursula Schmidt-Erfurth
- 关键词：Benchmark dataset ; Cyst segmentation ; SD-OCT
- 刊名：Computer Methods and Programs in Biomedicine
- 出版年：2016
- 出版时间：July 2016
- 年：2016
- 卷：130
- 期：Complete
- 页码：93-105
- 全文大小：3228 K
文摘
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A framework including data selection, task assignment and annotation combination stages for a confidence based benchmark dataset for retinal image processing is proposed.
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A novel task assignment is used to remove data and reader biases.
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The annotation of readers is combined based on their accuracy and performance.
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The framework is used to build a confidence based benchmark dataset for cyst segmentation.
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The generated benchmark can be used to reliably evaluate cyst segmentation methods.