Evidence map›Paper›PMID 41927822›Full record

ArticleJournal of imaging informatics in medicine2026

Residual Conditional Variational Autoencoder for Multi-Center PET/CT Radiomic Feature Harmonization with Integrated Modeling of Batch Effects and Clinical Covariates.

Bingzhen Wang, Jinghua Liu, Xiaolei Zhang, Zhongxiao Wang, Zhendong Cao, Tiange Liu, Hafiz Rashidi Harun Ramli, Hazreen Haizi Harith, Wan Zuha Wan Hasan, Xianling Dong

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Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Bingzhen WangDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Malaysia.
Jinghua LiuDepartment of Nursing, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia.
Xiaolei ZhangDepartment of Biomedical Engineering, Chengde Medical University, Chengde City, Hebei Province, China.
Zhongxiao WangDepartment of Biomedical Engineering, Chengde Medical University, Chengde City, Hebei Province, China.
Zhendong CaoDepartment of Radiology, The Affiliated Hospital of Chengde Medical University, Chengde City, Hebei Province, China.
Tiange LiuInstitute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China.
Hafiz Rashidi Harun RamliDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Malaysia.
Hazreen Haizi HarithDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Malaysia.
Wan Zuha Wan HasanDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia, Serdang, Malaysia. wanzuha@upm.edu.my.
Xianling DongDepartment of Biomedical Engineering, Chengde Medical University, Chengde City, Hebei Province, China. dongxl@cdmc.edu.cn.ORCID http://orcid.org/0009-0002-8787-8379

Funding

Chengde Biomedicine Industry Research Institute Funding project 202205B086Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences 202307Guizhou Provincial Youth Science and Technology Talents Growth Project BJK2023060Hebei Province Introduced Returned Overseas Chinese Scholars Funding Project C20220107Wellcome Trust 202404
6 · The paper itself

Abstract

This study proposes a Residual Conditional Variational Autoencoder model (ResCVAE-Harmonizer) that integrates batch information and clinical covariates for multi-center feature harmonization and systematically and comprehensively evaluates its harmonization performance. This study collected 806 cases from 9 different centers. After preprocessing, three types of features were extracted from PET and CT images: low-dimensional radiomic features, high-dimensional radiomic features, and deep learning features based on 3D-DenseNet-121. Each feature type was harmonized using ComBat, CovBat, and the proposed ResCVAE-Harmonizer. Both harmonized and original features were included in a comprehensive evaluation framework comprising variance homogeneity analysis, multi-center classification test, and downstream task effectiveness evaluation. The ResCVAE-Harmonizer significantly improved cross-center feature consistency. Levene's test results showed a general reduction in - log

Indexed as

CTHarmonizationMulti-centerPETRadiomics

Identifiers

PMID41927822

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.