Prediction of metastasis in head and neck cancer from computed tomography images

Tzu Yun Lo, Pei Yin Wei, Chia Heng Yen, Jiing Feng Lirng, Muh Hwa Yang, Pen Yuan Chu*, Shinn-Ying Ho

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The current medical method for determining whether the malignant tumor of the head and neck metastasizes to the lymph is to interpret the pathological section of the patient's lymph. This study proposes a support vector machine (SVM) based method Pred-Meta to predict metastasis of a malignant tumor from a patient's computed tomography (CT) image. Pred-Meta utilizes three feature types, including texture, morphology, and grayscale, and an optimal feature selection method cooperated with SVM. The data set consists of 75 samples from 70 patients in head and neck cancer provided by Taipei Veterans General Hospital of Taiwan with a record of lymphatic metastasis. Pred-Meta using leave-one-out cross-validation achieved 100% in predicting metastasis. The merit of the Pred-Meta method is its non-invasiveness and low cost. Auxiliary physicians screen out patients with high risk of diversion in the early stages to help plan treatment guidelines. The limitation of Pred-Meta suffers from the small number of training samples. It is expected that Pred-Meta would perform better in testing independent cohort when the number of training samples significantly increases.

Original languageEnglish
Title of host publicationProceedings of 2018 4th International Conference on Robotics and Artificial Intelligence, ICRAI 2018
PublisherAssociation for Computing Machinery
Pages18-23
Number of pages6
ISBN (Electronic)9781450365840
DOIs
StatePublished - 17 Nov 2018
Event4th International Conference on Robotics and Artificial Intelligence, ICRAI 2018 - Guangzhou, China
Duration: 17 Nov 201819 Nov 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Robotics and Artificial Intelligence, ICRAI 2018
CountryChina
CityGuangzhou
Period17/11/1819/11/18

Keywords

  • Head
  • Machine learning
  • Metastasis
  • Neck cancer
  • Support vector machine

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