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Adaptive patch sampling and location-aware reasoning for whole body PET-CT multi-organ segmentation.

Overview

Authors: Junha Park1, Arthur Cho2, Hae-Jeong Park1,2,3,4,5,6
  1. Yonsei University College of Medicine, Seoul, South Korea
  2. Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea
  3. Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, South Korea
  4. Department of Cognitive Science, Yonsei University, Seoul, South Korea
  5. Institute of Human Complexity and Systems Science, Yonsei University, Seoul, South Korea
  6. Epilepsy Research Institute, Brain research institute, Yonsei University, Seoul, South Korea
Institutions: Yonsei University (South Korea); Yonsei University Health System (South Korea)
Journal: Scientific reports, volume 16, issue 1, article 22461
Dates: received 17 February 2026; accepted 24 April 2026; published online 15 May 2026
Type: Research article · Language: English
License: CC BY-NC-ND
Identifiers: DOI 10.1038/s41598-026-51023-x · PMID 42141028 · PMCID PMC13377078 · OpenAlex W7161277039
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: PET / SPECT (modality), human (organism), methods / tools (subfield)
Methods: Smoothing, state filtering, decompositions, Machine learning, Connectivity
Keywords: Computational biology and bioinformatics, Mathematics and computing, Neuroscience
MeSH: Image Processing, Computer-Assisted*, Positron Emission Tomography Computed Tomography*, Whole Body Imaging*, Adaptive Algorithms, Algorithms, Humans, Neural Networks, Computer (* major topic)
Topic: Medical Image Segmentation Techniques (Computer Vision and Pattern Recognition, Computer Science), according to OpenAlex
Funding: National Research Foundation (NRF) funded by the Korean government (No. RS-2024-00401794); MD-PhD/Medical Scientist Training Program through the Korea Health Industry Development Institute; a Severance Hospital Research fund for Clinical excellence (C-2023-0020)
Citations: not cited yet (Europe PMC); 39 references in the paper

Abstract

The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.

Code

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Data

Datasets cited

Data availability statement

The paper has a data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:

Read it in the paper: doi.org/10.1038/s41598-026-51023-x.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 3 keywords, 7 MeSH terms, 3 funders, 9 references.

Cite

This paper

Park, J., Cho, A., & Park, H.-J. (2026). Adaptive patch sampling and location-aware reasoning for whole body PET-CT multi-organ segmentation. Scientific reports, 16(1), 22461. https://doi.org/10.1038/s41598-026-51023-x

BibTeX

@article{park2026adaptive,
author = {Park, Junha and Cho, Arthur and Park, Hae-Jeong},
title = {{Adaptive patch sampling and location-aware reasoning for whole body PET-CT multi-organ segmentation}},
journal = {Scientific reports},
year = {2026},
month = may,
volume = {16},
number = {1},
pages = {22461},
publisher = {Nature Publishing Group},
issn = {2045-2322},
doi = {10.1038/s41598-026-51023-x},
url = {https://doi.org/10.1038/s41598-026-51023-x},
pmid = {42141028},
pmcid = {PMC13377078}
}

RIS

TY - JOUR
AU - Park, Junha
AU - Cho, Arthur
AU - Park, Hae-Jeong
TI - Adaptive patch sampling and location-aware reasoning for whole body PET-CT multi-organ segmentation
T2 - Scientific reports
J2 - Sci Rep
PY - 2026
DA - 2026/05/15
VL - 16
IS - 1
SP - 22461
SN - 2045-2322
PB - Nature Publishing Group
DO - 10.1038/s41598-026-51023-x
UR - https://doi.org/10.1038/s41598-026-51023-x
LA - en
ER -

CSL-JSON

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