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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 polyp detection using SmartEndo-Net based on fusion feature pyramid network with mix-up edges

Autor: Young Jae Kim, Sohyun Byun, Choong-Il Ahn, Sang Wook Cho, Kwang Gi Kim

Publikováno v: Medical Imaging 2022: Computer-Aided Diagnosis.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8c882a1a2f9f20abd5a82a6a04e7b4a0
https://doi.org/10.1117/12.2612651

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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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