Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features

Masahiro Yamada, Hidetaka Arimura, Kenta Ninomiya, Mazen Soufi

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

Abstract

Histological subtypes, i.e. adenocarcinoma (ADN) and squamous cell carcinoma (SCC), identified from a single biopsy occasionally differ from those from actual surgical resections in NSCLC. For increasing the classification accuracy, we aim to develop an automated approach for classifying histological subtypes of NSCLC using Gaussian, linear and polynomial support vector machines (SVMs) with radiomic features. Classification models of Gaussian, linear and polynomial SVMs constructed with radiomic features achieved the areas under the curves of 0.7542, 0.7522 and 0.7531, respectively. Histological subtypes of NSCLC could be classified into ADN and SCC using a Gaussian SVM with radiomic features.

Original languageEnglish
Title of host publicationInternational Forum on Medical Imaging in Asia 2019
EditorsJong Hyo Kim, Hiroshi Fujita, Feng Lin
PublisherSPIE
ISBN (Electronic)9781510627758
DOIs
Publication statusPublished - Jan 1 2019
EventInternational Forum on Medical Imaging in Asia 2019 - Singapore, Singapore
Duration: Jan 7 2019Jan 9 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11050
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceInternational Forum on Medical Imaging in Asia 2019
CountrySingapore
CitySingapore
Period1/7/191/9/19

Fingerprint

Support vector machines
Support Vector Machine
polynomials
cancer
Polynomials
Polynomial
Biopsy
Cell
classifying
Curve
curves
Epithelial Cells
Model

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Yamada, M., Arimura, H., Ninomiya, K., & Soufi, M. (2019). Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features. In J. H. Kim, H. Fujita, & F. Lin (Eds.), International Forum on Medical Imaging in Asia 2019 [110500P] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11050). SPIE. https://doi.org/10.1117/12.2521511

Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features. / Yamada, Masahiro; Arimura, Hidetaka; Ninomiya, Kenta; Soufi, Mazen.

International Forum on Medical Imaging in Asia 2019. ed. / Jong Hyo Kim; Hiroshi Fujita; Feng Lin. SPIE, 2019. 110500P (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11050).

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

Yamada, M, Arimura, H, Ninomiya, K & Soufi, M 2019, Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features. in JH Kim, H Fujita & F Lin (eds), International Forum on Medical Imaging in Asia 2019., 110500P, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11050, SPIE, International Forum on Medical Imaging in Asia 2019, Singapore, Singapore, 1/7/19. https://doi.org/10.1117/12.2521511
Yamada M, Arimura H, Ninomiya K, Soufi M. Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features. In Kim JH, Fujita H, Lin F, editors, International Forum on Medical Imaging in Asia 2019. SPIE. 2019. 110500P. (Proceedings of SPIE - The International Society for Optical Engineering). https://doi.org/10.1117/12.2521511
Yamada, Masahiro ; Arimura, Hidetaka ; Ninomiya, Kenta ; Soufi, Mazen. / Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features. International Forum on Medical Imaging in Asia 2019. editor / Jong Hyo Kim ; Hiroshi Fujita ; Feng Lin. SPIE, 2019. (Proceedings of SPIE - The International Society for Optical Engineering).
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