이승학 프로필 사진

이승학

Lee, SeungHak

연구소

통일한국보건의학연구소

ORCID

연구분야

  • deep learning, 
  • machine learing, 
  • medical image process, 
  • 딥러닝, 
  • 머신러닝, 
  • 의료영상처리

자료 필터

자료유형

발행연도

2021 ~ 2026
2021 2026

키워드

언어

선택된 필터

  • article
  • conference
  • book

전체 9건 중 1번부터 9번까지의 결과를 표시합니다.

2026
2024
Article

Analysis of the association between vestibular schwannoma and hearing status using a newly developed radiomics technique

  • 2024-06
  • European Archives of Oto-Rhino-Laryngology
  • Springer Verlag
2022
Article

Robust multimodal fusion network using adversarial learning for brain tumor grading

  • Jeong, Seung-wan ; 
  • Cho, Hwan-ho ; 
  • Lee, Seunghak ; 
  • Park, Hyunjin
  • 2022-11
  • Computer Methods and Programs in Biomedicine
  • Elsevier BV
Article

Incremental benefits of size-zone matrix-based radiomics features for the prognosis of lung adenocarcinoma: advantage of spatial partitioning on tumor evaluation

  • Kim, Eunjin ; 
  • Lee, Geewon ; 
  • Lee, Seung-hak ; 
  • Cho, Hwanho ; 
  • Lee, Ho Yun ; 
  • 외 1명
  • 2022-11
  • European Radiology
  • Springer Verlag
2021
Article

Evaluation of Response to Immune Checkpoint Inhibitors Using a Radiomics, Lesion-Level Approach

  • Song, Chorog ; 
  • Park, Hyunjin ; 
  • Lee, Ho Yun ; 
  • Lee, SeungHak ; 
  • Ahn, Joong Hyun ; 
  • 외 1명
  • 2021-12
  • Cancers
  • Multidisciplinary Digital Publishing Institute (MDPI)
Article

Are radiomics features universally applicable to different organs?

  • Lee, S.-H. ; 
  • Cho, H.-H. ; 
  • Kwon, J. ; 
  • Lee, H.Y. ; 
  • Park, H.
  • 2021-04-07
  • Cancer Imaging
  • e-med
Article

Tumor Margin Contains Prognostic Information: Radiomic Margin Characteristics Analysis in Lung Adenocarcinoma Patients

  • Lee, Geewon ; 
  • Park, Hyunjin ; 
  • Lee, Ho Yun ; 
  • Ahn, Joong Hyun ; 
  • Sohn, Insuk ; 
  • ... Lee, Seung-Hak ; 
  • 외 1명
  • 2021-04
  • Cancers
  • Multidisciplinary Digital Publishing Institute (MDPI)