UNet‐based multi‐organ segmentation in photon counting CT using virtual monoenergetic images

The proposed method using VMIs improves training stability for multi-organ segmentation in PCCT, particularly when the number of energy bins is small.

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Publication Details

Journal
Medical Physics
Published
2024-10-07
DOI
https://doi.org/10.1002/mp.17440
Citations
6
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
1.11

Funders

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article

UNet‐based multi‐organ segmentation in photon counting CT using virtual monoenergetic images

Okkyun Lee, Dong Hye Ye, Sumin Baek
6 citations
Medical Physics
Advanced X-ray and CT Imaging
1.11
article

UNet‐based multi‐organ segmentation in photon counting CT using virtual monoenergetic images

Okkyun Lee, Dong Hye Ye, Sumin Baek
article en
6 citations

Abstract

The proposed method using VMIs improves training stability for multi-organ segmentation in PCCT, particularly when the number of energy bins is small.

Medical PhysicsVol. 52(1)
Georgia State University (US), Daegu Gyeongbuk Institute of Science and Technology (KR)
Institute for Information and Communications Technology Promotion
Affordable and clean energy
Openalex Percentile: Top 24%
Advanced X-ray and CT Imaging
1.11
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