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Prediction of Two-Year Recurrence-Free Survival in Operable NSCLC Patients Using Radiomic Features from Intra- and Size-Variant Peri-Tumoral Regions on Chest CT Images

Autor: Soomin Lee, Julip Jung, Helen Hong, Bong-Seog Kim

Publikováno v: Diagnostics, Vol 12, Iss 6, p 1313 (2022)

To predict the two-year recurrence-free survival of patients with non-small cell lung cancer (NSCLC), we propose a prediction model using radiomic features of the inner and outer regions of the tumor. The intratumoral region and the peritumoral regio

Externí odkaz: https://doaj.org/article/b78cbf571a4246288d6adf1cb859eb2c

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Lung tumor segmentation using dual-coupling net with shape prior based on lung and mediastinal window images from chest CT images

Autor: Sohyun, Byun, Julip, Jung, Helen, Hong, Bong-Seog, Kim

Publikováno v: Journal of X-Ray Science and Technology. 30:1067-1083

BACKGROUND: Volumetric lung tumor segmentation is difficult due to the diversity of the sizes, locations and shapes of lung tumors, as well as the similarity in the intensity with surrounding tissue structures. OBJECTIVE: We propose a dual-coupling n

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e8a959f7e375cc2e8aa2d9323ef34e6
https://doi.org/10.3233/xst-221191

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Automatic Segmentation of Lung Cancer in Chest CT Images through Capsule Network-based Dual-Window Ensemble Learning

Autor: Julip Jung, Jumin Lee, Helen Hong, Bong-Seog Kim

Publikováno v: Journal of KIISE. 48:905-912

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5660daae4339006c9b44d367ada39a8c
https://doi.org/10.5626/jok.2021.48.8.905

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CT quantification of the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis

Autor: Soon Ho Yoon, Helen Hong, Julip Jung, Heekyung Kim, Hyungjin Kim, Jin Mo Goo, Jeong Hwa Yoon, Junghoan Park

Publikováno v: European Radiology

Objectives To quantify the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis (IPF) using the Gaussian curvature analysis for evaluating disease severity and predicting survival. Methods We retrospectively included 104 IPF patients

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a20e3cbcc45c7fc5ef181e0de0ba79a
https://doi.org/10.1007/s00330-020-07594-y

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Radiomic feature-based prediction model of lung cancer recurrence in NSCLC patients

Autor: Helen Hong, Bongseok Kim, Julip Jung, Soomin Lee

Publikováno v: International Workshop on Advanced Imaging Technology (IWAIT) 2020.

This study investigates the potential of a radiomic feature-based prediction model of non-small cell lung cancer (NSCLC) recurrence within two years on chest CT images. First, tumor areas are defined as intra-tumoral areas that have been manually seg

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::202181932947d10e75d824ebe3fdf83b
https://doi.org/10.1117/12.2566451

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Uni- and Multi-Modal Radiomic Features for the Predicting Prostate Cancer Aggressiveness

Autor: Hansang Lee, Helen Hong, Julip Jung, Sung Il Hwang, Hak Jong Lee

Publikováno v: ISBI

The use of quantitative radiomic features of MRI to predict the aggressiveness of prostate cancer has attracted increasing amounts of attention due to its potential as anon-invasive biomarker for prostate cancer. In this study, to predict prostate ca

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::708675da3048a253dfac583f9ee8104c
https://doi.org/10.1109/isbi45749.2020.9098375

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Lung tumor segmentation using coupling-net with shape-focused prior on chest CT images of non-small cell lung cancer patients

Autor: Bong Seog Kim, Hoonil Oh, Helen Hong, Sohyun Byun, Julip Jung

Publikováno v: Medical Imaging 2020: Computer-Aided Diagnosis.

Volumetric lung tumor segmentation is essential for monitoring tumor response to treatment by tracking lung tumor changes. However, it is difficult to segment due to the diversity of size, shape, location as well as types such as solid, subsolid and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::121eb45b1677fb71e3e8f6a64e9e9685
https://doi.org/10.1117/12.2551280

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Automatic liver segmentation in abdominal CT images using combined 2.5D and 3D segmentation networks with high-score shape prior for radiotherapy treatment planning

Autor: Jin Sung Kim, Taesik Jeong, Helen Hong, Jinsil Seong, Julip Jung

Publikováno v: Medical Imaging 2020: Computer-Aided Diagnosis.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5602739b0367d4c3456bbe2b0eeb61cb
https://doi.org/10.1117/12.2551287

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Prediction of prostate cancer aggressiveness using quantitative radiomic features using multi-parametric MRI

Autor: Hak Jong Lee, Julip Jung, Sung Il Hwang, Helen Hong, Young Gi Kim

Publikováno v: Medical Imaging 2020: Computer-Aided Diagnosis.

The use of quantitative radiomic features of MRI to predict the aggressiveness of prostate cancer has attracted increasing amounts of attention due to its potential as a non-invasive biomarker for prostate cancer. Although clinical studies have shown

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::89bcc200ee9a1664e876bd1396ed0acd
https://doi.org/10.1117/12.2551298

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