Persistent homology analysis of longitudinal CT fibrotic features in COPD

PH can be used to quantify fibrotic lesions on CT and PH-fibrosis% could be a prognostic imaging marker in patients with COPD.

Authors

Institutions

Publication Details

Journal
European Respiratory Journal
Published
2026-02-26
DOI
https://doi.org/10.1183/13993003.01630-2025
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Persistent homology analysis of longitudinal CT fibrotic features in COPD

T Handa, Muro Shigeo, Motonari Fukui, Yoshihiro Seri et al.
European Respiratory Journal
Radiomics and Machine Learning in Medical Imaging
article

Persistent homology analysis of longitudinal CT fibrotic features in COPD

T Handa, Muro Shigeo, Motonari Fukui, Yoshihiro Seri, Susumu Sato, Yusuke Shiraishi, Tomoki Maetani, Ryo Sakamoto, Tsuyoshi Oguma, Kunihiko Terada, Toyohiro Hirai, Shizuo Kaji, Naoya Tanabe
article en

Abstract

PH can be used to quantify fibrotic lesions on CT and PH-fibrosis% could be a prognostic imaging marker in patients with COPD.

European Respiratory Journal
Kyoto University (JP), Kyoto City Hospital (JP), Kitano Hospital (JP), Nara Medical University (JP)
Good health and well-being
Openalex Percentile: Top 43%
Radiomics and Machine Learning in Medical Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.