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

Masahiro Yamada; Hidetaka Arimura; Kenta Ninomiya; Mazen Soufi

doi:10.1117/12.2521511

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

Masahiro Yamada, Hidetaka Arimura, Kenta Ninomiya, Mazen Soufi

Division of medical Quantum Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	International Forum on Medical Imaging in Asia 2019
Editors	Jong Hyo Kim, Hiroshi Fujita, Feng Lin
Publisher	SPIE
ISBN (Electronic)	9781510627758
DOIs	https://doi.org/10.1117/12.2521511
Publication status	Published - Jan 1 2019
Event	International Forum on Medical Imaging in Asia 2019 - Singapore, Singapore Duration: Jan 7 2019 → Jan 9 2019

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11050
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	International Forum on Medical Imaging in Asia 2019
Country	Singapore
City	Singapore
Period	1/7/19 → 1/9/19

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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 proceeding › Conference 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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10.1117/12.2521511