Convolutional Neural Network Classification of Basal Cell Carcinoma in Harmonically Generated Microscopy Images

Zheng Han Yu, Gwo Giun Chris Lee, Yihua Liao, Chi Kuang Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Basal cell carcinoma (BCC) is the most common form of skin cancer, which could cause local damage of nerves or tissues. Since the tumor growth of BCC is slow and not painful, it could lead to delayed tumor detection and hence necessary subsequent prompt intervention. This paper proposes a computer-aided diagnosis (CAD) method which uses the Gabor filter to extract characteristic scale information according to the characteristic of infected dendritic melanocytes in the third harmonic generation image. Scale information of image which is extracted from Gabor filter allows automatic adjustment of scale range and more accurate segmentation of the infected basal cells in medical images. Subsequently, normal and infected collagen fiber images are used to train convolution neural network (CNN) which are initialized with extracted features as kernels within convolution layers, resulting in high tumor detection accuracy and speed of convergence in harmonically generated microscopy (HGM) images. Experimental results show that this algorithm can accurately classify HGM images, with reduction in time and labor, and thus provides an efficient assisted tool in biomedical image analytics.

Original languageEnglish
Title of host publicationProceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages274-278
Number of pages5
ISBN (Electronic)9781665409964
DOIs
Publication statusPublished - 2022
Event4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022 - Incheon, Korea, Republic of
Duration: 2022 Jun 132022 Jun 15

Publication series

NameProceeding - IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022

Conference

Conference4th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2022
Country/TerritoryKorea, Republic of
CityIncheon
Period22-06-1322-06-15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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