Fully Automatic Prediction for Efficacy of Photodynamic Therapy in Clinical Port-Wine Stains Treatment: A Pilot Study

Fully Automatic Prediction for Efficacy of Photodynamic Therapy in Clinical Port-Wine Stains Treatment: A Pilot Study

In this paper, we report a fully automatic method for the prediction of the treatment efficacy of photodynamic therapy during the clinical treatment in port-wine stains. Histogram of oriented gradients (HOG) features were extracted from optical coherence tomography images. Isolation forest (iForest)...

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Bibliographic Details
Main Authors: Shengnan Ai, Chengming Wang, Wenxin Zhang, Jui-Cheng Hsieh, Zhengyu Chen, Bin He, Xiao Zhang, Ning Zhang, Ying Gu, Ping Xue
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Anomaly detection
machine learning
optical coherence tomography
port-wine stain
support vector data description
Online Access:https://ieeexplore.ieee.org/document/8986618/

Internet

https://ieeexplore.ieee.org/document/8986618/

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