Classification of squamous cell carcinoma from FF-OCT images: Data selection and progressive model construction
Journal
Computerized Medical Imaging and Graphics
Journal Volume
93
Date Issued
2021
Author(s)
Abstract
We investigate the speed and performance of squamous cell carcinoma (SCC) classification from full-field optical coherence tomography (FF-OCT) images based on the convolutional neural network (CNN). Due to the unique characteristics of SCC features, the high variety of CNN, and the high volume of our 3D FF-OCT dataset, progressive model construction is a time-consuming process. To address the issue, we develop a training strategy for data selection that makes model training 16 times faster by exploiting the dependency between images and the knowledge of SCC feature distribution. The speedup makes progressive model construction computationally feasible. Our approach further refines the regularization, channel attention, and optimization mechanism of SCC classifier and improves the accuracy of SCC classification to 87.12% at the image level and 90.10% at the tomogram level. The results are obtained by testing the proposed approach on an FF-OCT dataset with over one million mouse skin images. ? 2021 Elsevier Ltd
Subjects
Convolutional neural network
Deep learning
Optical coherence tomography
Regularization
Squamous cell carcinoma
Training strategy
Convolution
Convolutional neural networks
Data reduction
Deep neural networks
Image classification
Image enhancement
Large dataset
Statistical tests
Data Selection
Full-field optical coherence tomographies
Image data
Model construction
Progressive models
Regularisation
Optical tomography
Article
cancer classification
cancer diagnosis
classification algorithm
classifier
comparative study
computer assisted diagnosis
convolutional neural network
deep learning
diagnostic accuracy
feature selection
full field optical coherence tomography
human
optical coherence tomography
residual neural network
squamous cell skin carcinoma
three-dimensional imaging
animal
diagnostic imaging
mouse
squamous cell carcinoma
Animals
Carcinoma, Squamous Cell
Mice
Neural Networks, Computer
Tomography, Optical Coherence
SDGs
Type
journal article